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In machine learning (ML), a widespread claim is that the area under the precision-recall curve (AUPRC) is a superior metric for model comparison to the area under the receiver operating characteristic (AUROC) for tasks with class imbalance.
Lsac national longitudinal bar passage study. lsac research report series
Linda F Wightman · 1998
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The relationship between precision-recall and roc curves
Jesse Davis and Mark Goadrich · 2006
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Gleaner: Creating ensembles of first-order clauses to improve recall-precision curves
Mark Goadrich, Louis Oliphant, and Jude Shavlik · 2006
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Uci machine learning repository, 2007
Arthur Asuncion and David Newman · 2007
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Supervised reconstruction of biological networks with local models
Kevin Bleakley, Gérard Biau, and Jean-Philippe Vert · 2007
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Decision trees for hierarchical multi-label classification
Celine Vens, Jan Struyf, Leander Schietgat, Sašo Džeroski, and Hendrik Blockeel · 2008
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Wikipedia vandalism detection: Combining natural language, metadata, and reputation features
B Thomas Adler, Luca De Alfaro, Santiago M Mola-Velasco, Paolo Rosso, and Andrew G West · 2011
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Algorithms for hyper-parameter optimization
James Bergstra, Rémi Bardenet, Yoshua Bengio, and Balázs Kégl · 2011
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Random search for hyper-parameter optimization
James Bergstra and Yoshua Bengio · 2012
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Unachievable region in precision-recall space and its effect on empirical evaluation
Kendrick Boyd, Vitor Santos Costa, Jesse Davis, and C David Page · 2012
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Link prediction: fair and effective evaluation
Ryan Lichtnwalter and Nitesh V Chawla · 2012
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Statistical topic models for multi-label document classification
Timothy N Rubin, America Chambers, Padhraic Smyth, and Mark Steyvers · 2012
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Area under the precision-recall curve: point estimates and confidence intervals
Kendrick Boyd, Kevin H Eng, and C David Page · 2013
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Imbalanced learning: foundations, algorithms, and applications
Haibo He and Yunqian Ma · 2013
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Link prediction with social vector clocks
Conrad Lee, Bobo Nick, Ulrik Brandes, and Pádraig Cunningham · 2013
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An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics
Victoria López, Alberto Fernández, Salvador García, Vasile Palade, and Francisco Herrera · 2013
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Quantifying the multi-scale performance of network inference algorithms
Chris J Oates, Richard Amos, and Simon EF Spencer · 2014
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Gamma/hadron segregation for a ground based imaging atmospheric cherenkov telescope using machine learning methods: Random forest leads
Mradul Sharma, Jitadeepa Nayak, Maharaj Krishna Koul, Smarajit Bose, and Abhas Mitra · 2014
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Salient object detection: A benchmark
Ali Borji, Ming-Ming Cheng, Huaizu Jiang, and Jia Li · 2015
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A robust ensemble approach to learn from positive and unlabeled data using svm base models
Marc Claesen, Frank De Smet, Johan A.K. Suykens, and Bart De Moor · 2015
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Reconstructing subclonal composition and evolution from whole genome sequencing of tumors, 2015
Amit G. Deshwar, Shankar Vembu, Christina K. Yung, Gun Ho Jang, Lincoln Stein, and Quaid Morris · 2015
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Precision-recall-gain curves: Pr analysis done right
Peter Flach and Meelis Kull · 2015
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Mcode: Multivariate conditional outlier detection
Charmgil Hong and Milos Hauskrecht · 2015
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Estimating reproducibility in genome-wide association studies, 2015
Wei Jiang, Jing-Hao Xue, and Weichuan Yu · 2015
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Type-constrained representation learning in knowledge graphs
Denis Krompaß, Stephan Baier, and Volker Tresp · 2015
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Predicting deep zero-shot convolutional neural networks using textual descriptions
Jimmy Lei Ba, Kevin Swersky, Sanja Fidler, et al · 2015
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The precision–recall curve overcame the optimism of the receiver operating characteristic curve in rare diseases
Brice Ozenne, Fabien Subtil, and Delphine Maucort-Boulch · 2015
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Experimental study with real-world data for android app security analysis using machine learning
Sankardas Roy, Jordan DeLoach, Yuping Li, Nic Herndon, Doina Caragea, Xinming Ou, Venkatesh Prasad Ranganath, Hongmin Li, and Nicolais Guevara · 2015
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The precision-recall plot is more informative than the roc plot when evaluating binary classifiers on imbalanced datasets
Takaya Saito and Marc Rehmsmeier · 2015
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Fracking deep convolutional image descriptors, 2015
Edgar Simo-Serra, Eduard Trulls, Luis Ferraz, Iasonas Kokkinos, and Francesc Moreno-Noguer · 2015
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Evaluating link prediction methods
Yang Yang, Ryan N Lichtenwalter, and Nitesh V Chawla · 2015
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Threshold-free measures for assessing the performance of medical screening tests
Yan Yuan, Wanhua Su, and Mu Zhu · 2015
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Positive blood culture detection in time series data using a bilstm network, 2016
Leen De Baets, Joeri Ruyssinck, Thomas Peiffer, Johan Decruyenaere, Filip De Turck, Femke Ongenae, and Tom Dhaene · 2016
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Precision-recall curves, April 2016
Andreas Beger · 2016
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Xgboost: A scalable tree boosting system
Tianqi Chen and Carlos Guestrin · 2016
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Application of advanced record linkage techniques for complex population reconstruction
Peter Christen · 2016
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What can we learn from predictive modeling?, 2016
Skyler J. Cranmer and Bruce A. Desmarais · 2016
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Hierarchical hyperlink prediction for the www, 2016
Dario Garcia-Gasulla, Eduard Ayguadé, Jesús Labarta, Ulises Cortés, and Toyotaro Suzumura · 2016
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Mimic-iii, a freely accessible critical care database
Alistair EW Johnson, Tom J Pollard, Lu Shen, Li-wei H Lehman, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony Celi, and Roger G Mark · 2016
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Evaluating link prediction accuracy in dynamic networks with added and removed edges
Ruthwik R Junuthula, Kevin S Xu, and Vijay K Devabhaktuni · 2016
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Classification evaluation: It is important to understand both what a classification metric expresses and what it hides
Jake Lever · 2016
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Drug–target interaction prediction from pssm based evolutionary information
Zaynab Mousavian, Sahand Khakabimamaghani, Kaveh Kavousi, and Ali Masoudi-Nejad · 2016
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A review of relational machine learning for knowledge graphs
Maximilian Nickel, Kevin Murphy, Volker Tresp, and Evgeniy Gabrilovich · 2016
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Precrec: fast and accurate precision–recall and ROC curve calculations in R
Takaya Saito and Marc Rehmsmeier · 2016
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Fast learning of relational dependency networks
Oliver Schulte, Zhensong Qian, Arthur E Kirkpatrick, Xiaoqian Yin, and Yan Sun · 2016
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Using the weighted area under the net benefit curve for decision curve analysis
Rajesh Talluri and Sanjay Shete · 2016
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Deep over-sampling framework for classifying imbalanced data
Shin Ando and Chun Yuan Huang · 2017
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Hpatches: A benchmark and evaluation of handcrafted and learned local descriptors
Vassileios Balntas, Karel Lenc, Andrea Vedaldi, and Krystian Mikolajczyk · 2017
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Robust, deep and inductive anomaly detection
Raghavendra Chalapathy, Aditya Krishna Menon, and Sanjay Chawla · 2017
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Checkpoint ensembles: Ensemble methods from a single training process, 2017
Hugh Chen, Scott Lundberg, and Su-In Lee · 2017
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Ten quick tips for machine learning in computational biology
Davide Chicco · 2017
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Detecting gaze towards eyes in natural social interactions and its use in child assessment
Eunji Chong, Katha Chanda, Zhefan Ye, Audrey Southerland, Nataniel Ruiz, Rebecca M. Jones, Agata Rozga, and James M. Rehg · 2017
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A comparison of static, dynamic, and hybrid analysis for malware detection
Anusha Damodaran, Fabio Di Troia, Corrado Aaron Visaggio, Thomas H Austin, and Mark Stamp · 2017
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Anesthesiologist-level forecasting of hypoxemia with only spo2 data using deep learning, 2017
Gabriel Erion, Hugh Chen, Scott M. Lundberg, and Su-In Lee · 2017
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Multitask protein function prediction through task dissimilarity
Marco Frasca and Nicolo Cesa Bianchi · 2017
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A comparison of cnn-based face and head detectors for real-time video surveillance applications
Eric Granger, Madhu Kiran, Louis-Antoine Blais-Morin, et al · 2017
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Massive open online courses temporal profiling for dropout prediction
Tom Rolandus Hagedoorn and Gerasimos Spanakis · 2017
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A baseline for detecting misclassified and out-of-distribution examples in neural networks
Dan Hendrycks and Kevin Gimpel · 2017
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Automated visual fin identification of individual great white sharks
Benjamin Hughes and Tilo Burghardt · 2017
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Learning methods for dynamic topic modeling in automated behavior analysis
Olga Isupova, Danil Kuzin, and Lyudmila Mihaylova · 2017
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Recovering true classifier performance in positive-unlabeled learning
Shantanu Jain, Martha White, and Predrag Radivojac · 2017
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Aptrank: an adaptive pagerank model for protein function prediction on bi-relational graphs
Biaobin Jiang, Kyle Kloster, David F Gleich, and Michael Gribskov · 2017
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Experimental design trade-offs for gene regulatory network inference: An in silico study of the yeast saccharomyces cerevisiae cell cycle
Johan Markdahl, Nicolo Colombo, Johan Thunberg, and Jorge Gonçalves · 2017
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idti-esboost: identification of drug target interaction using evolutionary and structural features with boosting
Farshid Rayhan, Sajid Ahmed, Swakkhar Shatabda, Dewan Md Farid, Zaynab Mousavian, Abdollah Dehzangi, and M Sohel Rahman · 2017
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Comparison of two classifiers when the data sets are imbalanced: the power of the area under the precision-recall curve as the figure of merit versus the area under the ROC curve
Berkman Sahiner, Weijie Chen, Aria Pezeshk, and Nicholas Petrick · 2017
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Building automated vandalism detection tools for wikidata
Amir Sarabadani, Aaron Halfaker, and Dario Taraborelli · 2017
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Alignment of dynamic networks
V Vijayan, D Critchlow, and T Milenković · 2017
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A review of co-saliency detection technique: Fundamentals, applications, and challenges, 2017
Dingwen Zhang, Huazhu Fu, Junwei Han, Ali Borji, and Xuelong Li · 2017
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Two birds with one network: Unifying failure event prediction and time-to-failure modeling
Karan Aggarwal, Onur Atan, Ahmed K Farahat, Chi Zhang, Kosta Ristovski, and Chetan Gupta · 2018
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Improving palliative care with deep learning
Anand Avati, Kenneth Jung, Stephanie Harman, Lance Downing, Andrew Ng, and Nigam H Shah · 2018
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Found graph data and planted vertex covers
Austin R Benson and Jon Kleinberg · 2018
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Hybrid gradient boosting trees and neural networks for forecasting operating room data, 2018
Hugh Chen, Scott Lundberg, and Su-In Lee · 2018
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Mime: Multilevel medical embedding of electronic health records for predictive healthcare
Edward Choi, Cao Xiao, Walter F. Stewart, and Jimeng Sun · 2018
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Multi-label robust factorization autoencoder and its application in predicting drug-drug interactions, 2018
Xu Chu, Yang Lin, Jingyue Gao, Jiangtao Wang, Yasha Wang, and Leye Wang · 2018
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The effectiveness of multitask learning for phenotyping with electronic health records data
Daisy Yi Ding, Chloé Simpson, Stephen Pfohl, Dave C Kale, Kenneth Jung, and Nigam H Shah · 2018
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The accuracy, fairness, and limits of predicting recidivism
Julia Dressel and Hany Farid · 2018
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Enhancement of land-use change modeling using convolutional neural networks and convolutional denoising autoencoders, 2018
Guodong Du, Liang Yuan, Kong Joo Shin, and Shunsuke Managi · 2018
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Bohb: Robust and efficient hyperparameter optimization at scale
Stefan Falkner, Aaron Klein, and Frank Hutter · 2018
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Learning from imbalanced data sets
Alberto Fernández, Salvador García, Mikel Galar, Ronaldo C Prati, Bartosz Krawczyk, and Francisco Herrera · 2018
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Deep anomaly detection using geometric transformations
Izhak Golan and Ran El-Yaniv · 2018
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Automated software vulnerability detection with machine learning, 2018
Jacob A. Harer, Louis Y. Kim, Rebecca L. Russell, Onur Ozdemir, Leonard R. Kosta, Akshay Rangamani, Lei H. Hamilton, Gabriel I. Centeno, Jonathan R. Key, Paul M. Ellingwood, Erik Antelman, Alan Mackay, Marc W. McConley, Jeffrey M. Opper, Peter Chin, and Tomo Lazovich · 2018
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Asymmetric loss functions and deep densely-connected networks for highly-imbalanced medical image segmentation: Application to multiple sclerosis lesion detection
Seyed Raein Hashemi, Seyed Sadegh Mohseni Salehi, Deniz Erdogmus, Sanjay P Prabhu, Simon K Warfield, and Ali Gholipour · 2018
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Mdgan: Boosting anomaly detection using multi-discriminator generative adversarial networks, 2018
Yotam Intrator, Gilad Katz, and Asaf Shabtai · 2018
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Co-salient object detection based on deep saliency networks and seed propagation over an integrated graph
Dong-ju Jeong, Insung Hwang, and Nam Ik Cho · 2018
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Flare prediction using photospheric and coronal image data
Eric Jonas, Monica Bobra, Vaishaal Shankar, J Todd Hoeksema, and Benjamin Recht · 2018
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Semisupervised learning on heterogeneous graphs and its applications to facebook news feed, 2018
Cheng Ju, James Li, Bram Wasti, and Shengbo Guo · 2018
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An overview of deep learning based methods for unsupervised and semi-supervised anomaly detection in videos
B. Ravi Kiran, Dilip Mathew Thomas, and Ranjith Parakkal · 2018
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Mammo: A deep learning solution for facilitating radiologist-machine collaboration in breast cancer diagnosis, 2018
Trent Kyono, Fiona J. Gilbert, and Mihaela van der Schaar · 2018
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Rare events in the icu: an emerging challenge in classification and prediction
Daniel E Leisman · 2018
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Semi-supervised rare disease detection using generative adversarial network, 2018
Wenyuan Li, Yunlong Wang, Yong Cai, Corey Arnold, Emily Zhao, and Yilian Yuan · 2018
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Disease-atlas: Navigating disease trajectories using deep learning
Bryan Lim and Mihaela van der Schaar · 2018
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Predictive uncertainty estimation via prior networks
Andrey Malinin and Mark Gales · 2018
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Bridging the gap: Simultaneous fine tuning for data re-balancing
John McKay, Isaac Gerg, and Vishal Monga · 2018
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Utilizing device-level demand forecasting for flexibility markets-full version
Bijay Neupane, Torben Bach Pedersen, and Bo Thiesson · 2018
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Classification uncertainty of deep neural networks based on gradient information
Philipp Oberdiek, Matthias Rottmann, and Hanno Gottschalk · 2018
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Machine learning search for variable stars
Ilya N Pashchenko, Kirill V Sokolovsky, and Panagiotis Gavras · 2018
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End-to-end learning for music audio tagging at scale
Jordi Pons, Oriol Nieto, Matthew Prockup, Erik Schmidt, Andreas Ehmann, and Xavier Serra · 2018
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Dylink2vec: Effective feature representation for link prediction in dynamic networks, 2018
Mahmudur Rahman, Tanay Kumar Saha, Mohammad Al Hasan, Kevin S. Xu, and Chandan K. Reddy · 2018
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Fully automated segmentation of hyperreflective foci in optical coherence tomography images, 2018
Thomas Schlegl, Hrvoje Bogunovic, Sophie Klimscha, Philipp Seeböck, Amir Sadeghipour, Bianca Gerendas, Sebastian M. Waldstein, Georg Langs, and Ursula Schmidt-Erfurth · 2018
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Modeling irregularly sampled clinical time series, 2018
Satya Narayan Shukla and Benjamin M. Marlin · 2018
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Progressive boosting for class imbalance and its application to face re-identification
Roghayeh Soleymani, Eric Granger, and Giorgio Fumera · 2018
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A blended deep learning approach for predicting user intended actions
Fei Tan, Zhi Wei, Jun He, Xiang Wu, Bo Peng, Haoran Liu, and Zhenyu Yan · 2018
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Moleculenet: a benchmark for molecular machine learning
Zhenqin Wu, Bharath Ramsundar, Evan N Feinberg, Joseph Gomes, Caleb Geniesse, Aneesh S Pappu, Karl Leswing, and Vijay Pande · 2018
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Mitigating unwanted biases with adversarial learning
Brian Hu Zhang, Blake Lemoine, and Margaret Mitchell · 2018
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Variable Selection via Penalized Credible Regions with Dirichlet–Laplace Global-Local Shrinkage Priors
Yan Zhang and Howard D. Bondell · 2018
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Liuboost: locality informed under-boosting for imbalanced data classification
Sajid Ahmed, Farshid Rayhan, Asif Mahbub, Md Rafsan Jani, Swakkhar Shatabda, and Dewan Md Farid · 2019
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Inferring short-term volatility indicators from the bitcoin blockchain
Nino Antulov-Fantulin, Dijana Tolic, Matija Piskorec, Zhang Ce, and Irena Vodenska · 2019
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Data augmentation by autoencoders for unsupervised anomaly detection, 2019
Kasra Babaei, ZhiYuan Chen, and Tomas Maul · 2019
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Variational inference for sparse network reconstruction from count data
Julien Chiquet, Stephane Robin, and Mahendra Mariadassou · 2019
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Pocketcare: Tracking the flu with mobile phones using partial observations of proximity and symptoms
Wen Dong, Tong Guan, Bruno Lepri, and Chunming Qiao · 2019
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Estimating probabilistic context-free grammars for proteins using contact map constraints
Witold Dyrka, Mateusz Pyzik, François Coste, and Hugo Talibart · 2019
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Learning interpretable disease self-representations for drug repositioning, 2019
Fabrizio Frasca, Diego Galeano, Guadalupe Gonzalez, Ivan Laponogov, Kirill Veselkov, Alberto Paccanaro, and Michael M. Bronstein · 2019
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Positive and unlabeled learning through negative selection and imbalance-aware classification, 2019
Marco Frasca and Nicolò Cesa-Bianchi · 2019
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Packet2vec: Utilizing word2vec for feature extraction in packet data
Eric Goodman, Chase Zimmerman, and Corey Hudson · 2019
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Multitask learning and benchmarking with clinical time series data
Hrayr Harutyunyan, Hrant Khachatrian, David C Kale, Greg Ver Steeg, and Aram Galstyan · 2019
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Multitask learning and benchmarking with clinical time series data
Hrayr Harutyunyan, Hrant Khachatrian, David C. Kale, Greg Ver Steeg, and Aram Galstyan · 2019
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Deep anomaly detection with outlier exposure
Dan Hendrycks, Mantas Mazeika, and Thomas Dietterich · 2019
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Towards structured evaluation of deep neural network supervisors
Jens Henriksson, Christian Berger, Markus Borg, Lars Tornberg, Cristofer Englund, Sankar Raman Sathyamoorthy, and Stig Ursing · 2019
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Rdpd: Rich data helps poor data via imitation
Shenda Hong, Cao Xiao, Trong Nghia Hoang, Tengfei Ma, Hongyan Li, and Jimeng Sun · 2019
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Mina: Multilevel knowledge-guided attention for modeling electrocardiography signals
Shenda Hong, Cao Xiao, Tengfei Ma, Hongyan Li, and Jimeng Sun · 2019
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Gene regulatory network inference: an introductory survey
Vân Anh Huynh-Thu and Guido Sanguinetti · 2019
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Remote sensor design for visual recognition with convolutional neural networks
Lucas Jaffe, Michael Zelinski, and Wesam Sakla · 2019
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A unified neural network approach to e-commerce relevance learning
Yunjiang Jiang, Yue Shang, Rui Li, Wen-Yun Yang, Guoyu Tang, Chaoyi Ma, Yun Xiao, and Eric Zhao · 2019
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Drug-drug interaction prediction based on knowledge graph embeddings and convolutional-lstm network
Md Rezaul Karim, Michael Cochez, Joao Bosco Jares, Mamtaz Uddin, Oya Beyan, and Stefan Decker · 2019
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Finding dory in the crowd: Detecting social interactions using multi-modal mobile sensing
Kleomenis Katevas, Katrin H"̈ansel, Richard Clegg, Ilias Leontiadis, Hamed Haddadi, and Laurissa Tokarchuk · 2019
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General classification of light curves using extreme boosting, 2019
Refilwe Kgoadi, Chris Engelbrecht, Ian Whittingham, and Andrew Tkachenko · 2019
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High-throughput machine learning from electronic health records, 2019
Ross S. Kleiman, Paul S. Bennett, Peggy L. Peissig, Richard L. Berg, Zhaobin Kuang, Scott J. Hebbring, Michael D. Caldwell, and David Page · 2019
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Data-driven model for the identification of the rock type at a drilling bit
Nikita Klyuchnikov, Alexey Zaytsev, Arseniy Gruzdev, Georgiy Ovchinnikov, Ksenia Antipova, Leyla Ismailova, Ekaterina Muravleva, Evgeny Burnaev, Artyom Semenikhin, Alexey Cherepanov, et al · 2019
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Addressing delayed feedback for continuous training with neural networks in ctr prediction
Sofia Ira Ktena, Alykhan Tejani, Lucas Theis, Pranay Kumar Myana, Deepak Dilipkumar, Ferenc Huszár, Steven Yoo, and Wenzhe Shi · 2019
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Scaling structural learning with no-bears to infer causal transcriptome networks
Hao-Chih Lee, Matteo Danieletto, Riccardo Miotto, Sarah T Cherng, and Joel T Dudley · 2019
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Bi-directional lattice recurrent neural networks for confidence estimation
Qiujia Li, PM Ness, Anton Ragni, and Mark JF Gales · 2019
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Multiple perspectives hmm-based feature engineering for credit card fraud detection
Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Sylvie Calabretto, Olivier Caelen, Liyun He-Guelton, and Michael Granitzer · 2019
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Cross-referencing using fine-grained topic modeling
Jeffrey Lund, Piper Armstrong, Wilson Fearn, Stephen Cowley, Emily Hales, and Kevin Seppi · 2019
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Sunil Mallya, Marc Overhage, Sravan Bodapati, Navneet Srivastava, and Sahika Genc · 2019
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Targeted display advertising: the case of preferential attachment
Saurav Manchanda, Pranjul Yadav, Khoa Doan, and S Sathiya Keerthi · 2019
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Protrank: bypassing the imputation of missing values in differential expression analysis of proteomic data
Matúš Medo, Daniel M Aebersold, and Michaela Medová · 2019
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Evaluating merging strategies for sampling-based uncertainty techniques in object detection
Dimity Miller, Feras Dayoub, Michael Milford, and Niko S"̈underhauf · 2019
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Inferential approaches for network analysis: Amen for latent factor models
Shahryar Minhas, Peter D Hoff, and Michael D Ward · 2019
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Affectnet: A database for facial expression, valence, and arousal computing in the wild
Ali Mollahosseini, Behzad Hasani, and Mohammad H. Mahoor · 2019
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Early recognition of sepsis with gaussian process temporal convolutional networks and dynamic time warping
Michael Moor, Max Horn, Bastian Rieck, Damian Roqueiro, and Karsten Borgwardt · 2019
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Class imbalance techniques for high energy physics
Christopher W Murphy · 2019
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Rapid: early classification of explosive transients using deep learning
Daniel Muthukrishna, Gautham Narayan, Kaisey S Mandel, Rahul Biswas, and Renée Hložek · 2019
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Scalable and interpretable one-class svms with deep learning and random fourier features
Minh-Nghia Nguyen and Ngo Anh Vien · 2019
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Deep anomaly detection with deviation networks
Guansong Pang, Chunhua Shen, and Anton Van Den Hengel · 2019
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Link persistence and conditional distances in multiplex networks
Fragkiskos Papadopoulos and Kaj-Kolja Kleineberg · 2019
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Inductive logic programming via differentiable deep neural logic networks
Ali Payani and Faramarz Fekri · 2019
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Temporal self-attention network for medical concept embedding
Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Jing Jiang, and Michael Blumenstein · 2019
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Drug-drug interaction predicting by neural network using integrated similarity
Narjes Rohani and Changiz Eslahchi · 2019
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Graph-based selective outlier ensembles
Hamed Sarvari, Carlotta Domeniconi, and Giovanni Stilo · 2019
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A feature learning approach based on xgboost for driving assessment and risk prediction
Xiupeng Shi, Yiik Diew Wong, Michael Zhi-Feng Li, Chandrasekar Palanisamy, and Chen Chai · 2019
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An evaluation toolkit to guide model selection and cohort definition in causal inference, 2019
Yishai Shimoni, Ehud Karavani, Sivan Ravid, Peter Bak, Tan Hung Ng, Sharon Hensley Alford, Denise Meade, and Yaara Goldschmidt · 2019
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Minimizing the societal cost of credit card fraud with limited and imbalanced data, 2019
Samuel Showalter and Zhixin Wu · 2019
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Sensitivity analysis of deep neural networks
Hai Shu and Hongtu Zhu · 2019
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Interpolation-prediction networks for irregularly sampled time series
Satya Narayan Shukla and Benjamin Marlin · 2019
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Unsupervised contextual anomaly detection using joint deep variational generative models, 2019
Yaniv Shulman · 2019
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A context-aware framework for detecting sensor-based threats on smart devices
Amit Kumar Sikder, Hidayet Aksu, and A Selcuk Uluagac · 2019
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Putworkbench: Analysing privacy in ai-intensive systems, 2019
Saurabh Srivastava, Vinay P. Namboodiri, and T. V. Prabhakar · 2019
Metrics for benchmarking and uncertainty quantification: Quality, applicability, and best practices for machine learning in chemistry
Gaurav Vishwakarma, Aditya Sonpal, and Johannes Hachmann · 2021
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Fail-safe execution of deep learning based systems through uncertainty monitoring
Michael Weiss and Paolo Tonella · 2021
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As easy as apc: overcoming missing data and class imbalance in time series with self-supervised learning
Fiorella Wever, T Anderson Keller, Laura Symul, and Victor Garcia · 2021
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Semi-supervised music tagging transformer, 2021
Minz Won, Keunwoo Choi, and Xavier Serra · 2021
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Deep auc maximization for medical image classification: Challenges and opportunities, 2021
Tianbao Yang · 2021
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Classifying multilingual user feedback using traditional machine learning and deep learning
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Enhanced machine learning techniques for early harq feedback prediction in 5g
Nils Strodthoff, Baris Goktepe, Thomas Schierl, Cornelius Hellge, and Wojciech Samek · 2019
Cited alongside, same era.
Rankmerging: a supervised learning-to-rank framework to predict links in large social networks
Lionel Tabourier, Daniel F Bernardes, Anne-Sophie Libert, and Renaud Lambiotte · 2019
Cited alongside, same era.
Multimodal machine learning-based knee osteoarthritis progression prediction from plain radiographs and clinical data
Aleksei Tiulpin, Stefan Klein, Sita MA Bierma-Zeinstra, Jérôme Thevenot, Esa Rahtu, Joyce van Meurs, Edwin HG Oei, and Simo Saarakkala · 2019
Cited alongside, same era.
Clinical concept extraction for document-level coding
Sarah Wiegreffe, Edward Choi, Sherry Yan, Jimeng Sun, and Jacob Eisenstein · 2019
Cited alongside, same era.
Toward interpretable music tagging with self-attention, 2019
Minz Won, Sanghyuk Chun, and Xavier Serra · 2019
Cited alongside, same era.
Early icu mortality prediction and survival analysis for respiratory failure, 2021
Yilin Yin and Chun-An Chou · 2021
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Deep learning for insider threat detection: Review, challenges and opportunities
Shuhan Yuan and Xintao Wu · 2021
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Vpr-bench: An open-source visual place recognition evaluation framework with quantifiable viewpoint and appearance change
Mubariz Zaffar, Sourav Garg, Michael Milford, Julian Kooij, David Flynn, Klaus McDonald-Maier, and Shoaib Ehsan · 2021
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Segmenting microcalcifications in mammograms and its applications
Roee Zamir, Shai Bagon, David Samocha, Yael Yagil, Ronen Basri, Miri Sklair-Levy, and Meirav Galun · 2021
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Draem-a discriminatively trained reconstruction embedding for surface anomaly detection
Vitjan Zavrtanik, Matej Kristan, and Danijel Skočaj · 2021
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Grasp: Generic framework for health status representation learning based on incorporating knowledge from similar patients
Chaohe Zhang, Xin Gao, Liantao Ma, Yasha Wang, Jiangtao Wang, and Wen Tang · 2021
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Non-i.i.d. multi-instance learning for predicting instance and bag labels using variational auto-encoder, 2021
Weijia Zhang · 2021
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Nondiagonal mixture of dirichlet network distributions for analyzing a stock ownership network
Wenning Zhang, Ryohei Hisano, Takaaki Ohnishi, and Takayuki Mizuno · 2021
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A benchmark for studying diabetic retinopathy: Segmentation, grading, and transferability
Yi Zhou, Boyang Wang, Lei Huang, Shanshan Cui, and Ling Shao · 2021
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Machine learning to assess relatedness: the advantage of using firm-level data
Giambattista Albora and Andrea Zaccaria · 2022
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A revealing large-scale evaluation of unsupervised anomaly detection algorithms, 2022
Maxime Alvarez, Jean-Charles Verdier, D’Jeff K. Nkashama, Marc Frappier, Pierre-Martin Tardif, and Froduald Kabanza · 2022
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Machine learning methods for prediction of cancer driver genes: a survey paper
Renan Andrades and Mariana Recamonde-Mendoza · 2022
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Machine bias
Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner · 2022
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An efficient and scalable collection of fly-inspired voting units for visual place recognition in changing environments
Bruno Arcanjo, Bruno Ferrarini, Michael Milford, Klaus D McDonald-Maier, and Shoaib Ehsan · 2022
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The importance of future information in credit card fraud detection
Van Bach Nguyen, Kanishka Ghosh Dastidar, Michael Granitzer, and Wissam Siblini · 2022
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An approach for link prediction in directed complex networks based on asymmetric similarity-popularity, 2022
Hafida Benhidour, Lama Almeshkhas, and Said Kerrache · 2022
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Supervised contrastive learning to classify paranasal anomalies in the maxillary sinus
Debayan Bhattacharya, Benjamin Tobias Becker, Finn Behrendt, Marcel Bengs, Dirk Beyersdorff, Dennis Eggert, Elina Petersen, Florian Jansen, Marvin Petersen, Bastian Cheng, et al · 2022
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Saptarshi Chakraborty, Zoe Guan, Colin B Begg, and Ronglai Shen · 2022
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Asymptotically unbiased estimation for delayed feedback modeling via label correction
Yu Chen, Jiaqi Jin, Hui Zhao, Pengjie Wang, Guojun Liu, Jian Xu, and Bo Zheng · 2022
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A hybrid ensemble feature selection design for candidate biomarkers discovery from transcriptome profiles
Felipe Colombelli, Thayne Woycinck Kowalski, and Mariana Recamonde-Mendoza · 2022
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F1 score vs roc auc vs accuracy vs pr auc: Which evaluation metric should you choose?, July 2022
Jakub Czakon · 2022
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Algorithmic fairness datasets: the story so far
Alessandro Fabris, Stefano Messina, Gianmaria Silvello, and Gian Antonio Susto · 2022
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Probing contextual diversity for dense out-of-distribution detection, 2022
Silvio Galesso, Maria Alejandra Bravo, Mehdi Naouar, and Thomas Brox · 2022
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Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow
Aurélien Géron · 2022
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Machine learning modeling of family wide enzyme-substrate specificity screens
Samuel Goldman, Ria Das, Kevin K. Yang, and Connor W. Coley · 2022
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Prediction of hereditary cancers using neural networks
Zoe Guan, Giovanni Parmigiani, Danielle Braun, and Lorenzo Trippa · 2022
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Scaling out-of-distribution detection for real-world settings
Dan Hendrycks, Steven Basart, Mantas Mazeika, Andy Zou, Joseph Kwon, Mohammadreza Mostajabi, Jacob Steinhardt, and Dawn Song · 2022
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On evaluation metrics for medical applications of artificial intelligence
Steven A Hicks, Inga Strümke, Vajira Thambawita, Malek Hammou, Michael A Riegler, Pål Halvorsen, and Sravanthi Parasa · 2022
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Linevd: Statement-level vulnerability detection using graph neural networks
David Hin, Andrey Kan, Huaming Chen, and M Ali Babar · 2022
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Nlp-based classification of software tools for metagenomics sequencing data analysis into edam semantic annotation, 2022
Kaoutar Daoud Hiri, Matjaž Hren, and Tomaž Curk · 2022
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Increasing adversarial uncertainty to scale private similarity testing
Yiqing Hua, Armin Namavari, Kaishuo Cheng, Mor Naaman, and Thomas Ristenpart · 2022
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Density-aware personalized training for risk prediction in imbalanced medical data
Zepeng Huo, Xiaoning Qian, Shuai Huang, Zhangyang Wang, and Bobak J Mortazavi · 2022
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Next day wildfire spread: A machine learning dataset to predict wildfire spreading from remote-sensing data
Fantine Huot, R. Lily Hu, Nita Goyal, Tharun Sankar, Matthias Ihme, and Yi-Fan Chen · 2022
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Fraud detection using optimized machine learning tools under imbalance classes
Mary Isangediok and Kelum Gajamannage · 2022
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Towards textual out-of-domain detection without in-domain labels
Di Jin, Shuyang Gao, Seokhwan Kim, Yang Liu, and Dilek Hakkani-Tür · 2022
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What makes you change your mind? an empirical investigation in online group decision-making conversations, 2022
Georgi Karadzhov, Tom Stafford, and Andreas Vlachos · 2022
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A complex network based graph embedding method for link prediction, 2022
Said Kerrache and Hafida Benhidour · 2022
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Estimation of photometric redshifts. ii. identification of out-of-distribution data with neural networks
Joongoo Lee and Min-Su Shin · 2022
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Seamless lightning nowcasting with recurrent-convolutional deep learning
Jussi Leinonen, Ulrich Hamann, and Urs Germann · 2022
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Improving confidence estimation on out-of-domain data for end-to-end speech recognition
Qiujia Li, Yu Zhang, David Qiu, Yanzhang He, Liangliang Cao, and Philip C Woodland · 2022
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Multi-label sampling based on local label imbalance
Bin Liu, Konstantinos Blekas, and Grigorios Tsoumakas · 2022
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Multiple similarity drug–target interaction prediction with random walks and matrix factorization
Bin Liu, Dimitrios Papadopoulos, Fragkiskos D Malliaros, Grigorios Tsoumakas, and Apostolos N Papadopoulos · 2022
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Predicting intraoperative hypoxemia with hybrid inference sequence autoencoder networks
Hanyang Liu, Michael Montana, Dingwen Li, Chase Renfroe, Thomas Kannampallil, and Chenyang Lu · 2022
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Machine learning for dynamically predicting the onset of renal replacement therapy in chronic kidney disease patients using claims data
Daniel Lopez-Martinez, Christina Chen, and Ming-Jun Chen · 2022
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Instability in clinical risk stratification models using deep learning
Daniel Lopez-Martinez, Alex Yakubovich, Martin Seneviratne, Adam D. Lelkes, Akshit Tyagi, Jonas Kemp, Ethan Steinberg, N. Lance Downing, Ron C. Li, Keith E. Morse, Nigam H. Shah, and Ming-Jun Chen · 2022
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Medfact: Modeling medical feature correlations in patient health representation learning via feature clustering, 2022
Xinyu Ma, Xu Chu, Yasha Wang, Hailong Yu, Liantao Ma, Wen Tang, and Junfeng Zhao · 2022
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Real-time driver monitoring systems through modality and view analysis
Yiming Ma, Victor Sanchez, Soodeh Nikan, Devesh Upadhyay, Bhushan Atote, and Tanaya Guha · 2022
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A multimodal approach for multi-label movie genre classification
Rafael B Mangolin, Rodolfo M Pereira, Alceu S Britto Jr, Carlos N Silla Jr, Valéria D Feltrim, Diego Bertolini, and Yandre MG Costa · 2022
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Multiple inputs neural networks for fraud detection
Mansour Zoubeirou A Mayaki and Michel Riveill · 2022
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Squeeze flow of micro-droplets: convolutional neural network with trainable and tunable refinement, 2022
Aryan Mehboudi, Shrawan Singhal, and S. V. Sreenivasan · 2022
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Audio feature ranking for sound-based covid-19 patient detection
Julia A Meister, Khuong An Nguyen, and Zhiyuan Luo · 2022
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Precision–recall curve (prc) classification trees
Jiaju Miao and Wei Zhu · 2022
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Flicu: A federated learning workflow for intensive care unit mortality prediction
Lena Mondrejevski, Ioanna Miliou, Annaclaudia Montanino, David Pitts, Jaakko Hollmén, and Panagiotis Papapetrou · 2022
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Impact of class imbalance on chest x-ray classifiers: towards better evaluation practices for discrimination and calibration performance, 2022
Candelaria Mosquera, Luciana Ferrer, Diego Milone, Daniel Luna, and Enzo Ferrante · 2022
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A point process model for rare event detection, 2022
Santhosh Narayanan, Carsten Maple, and Mark Hooper · 2022
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Human readable network troubleshooting based on anomaly detection and feature scoring
Jose M Navarro, Alexis Huet, and Dario Rossi · 2022
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Structure-based approach to identifying small sets of driver nodes in biological networks
Eli Newby, Jorge Gómez Tejeda Zañudo, and Réka Albert · 2022
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Social network analytics for supervised fraud detection in insurance
María Óskarsdóttir, Waqas Ahmed, Katrien Antonio, Bart Baesens, Rémi Dendievel, Tom Donas, and Tom Reynkens · 2022
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Word-level text highlighting of medical texts for telehealth services
Ozan Ozyegen, Devika Kabe, and Mucahit Cevik · 2022
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Unsupervised anomaly and change detection with multivariate gaussianization
José A. Padrón-Hidalgo, Valero Laparra, and Gustau Camps-Valls · 2022
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Consistency-based self-supervised learning for temporal anomaly localization
Aniello Panariello, Angelo Porrello, Simone Calderara, and Rita Cucchiara · 2022
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Machine learning-based covid-19 patients triage algorithm using patient-generated health data from nationwide multicenter database
Min Sue Park, Hyeontae Jo, Haeun Lee, Se Young Jung, and Hyung Ju Hwang · 2022
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Net benefit, calibration, threshold selection, and training objectives for algorithmic fairness in healthcare
Stephen Pfohl, Yizhe Xu, Agata Foryciarz, Nikolaos Ignatiadis, Julian Genkins, and Nigam Shah · 2022
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Towards structuring real-world data at scale: Deep learning for extracting key oncology information from clinical text with patient-level supervision, 2022
Sam Preston, Mu Wei, Rajesh Rao, Robert Tinn, Naoto Usuyama, Michael Lucas, Roshanthi Weerasinghe, Soohee Lee, Brian Piening, Paul Tittel, Naveen Valluri, Tristan Naumann, Carlo Bifulco, and Hoifung Poon · 2022
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Modelling graph dynamics in fraud detection with Attention, 2022
Susie Xi Rao, Clémence Lanfranchi, Shuai Zhang, Zhichao Han, Zitao Zhang, Wei Min, Mo Cheng, Yinan Shan, Yang Zhao, and Ce Zhang · 2022
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Detecting irregular network activity with adversarial learning and expert feedback
Gopikrishna Rathinavel, Nikhil Muralidhar, Timothy O’Shea, and Naren Ramakrishnan · 2022
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Exploring traditional machine learning for identification of pathological auscultations, 2022
Haroldas Razvadauskas, Evaldas Vaiciukynas, Kazimieras Buskus, Lukas Drukteinis, Lukas Arlauskas, Saulius Sadauskas, and Albinas Naudziunas · 2022
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Feature extraction with spectral clustering for gene function prediction using hierarchical multi-label classification
Miguel Romero, Oscar Ramírez, Jorge Finke, and Camilo Rocha · 2022
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Imbalanced data? stop using roc-auc and use auprc instead, June 2022
Daniel Rosenberg · 2022
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Data-centric ai approach to improve optic nerve head segmentation and localization in oct en face images, 2022
Thomas Schlegl, Heiko Stino, Michael Niederleithner, Andreas Pollreisz, Ursula Schmidt-Erfurth, Wolfgang Drexler, Rainer A. Leitgeb, and Tilman Schmoll · 2022
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No pattern, no recognition: a survey about reproducibility and distortion issues of text clustering and topic modeling, 2022
Marília Costa Rosendo Silva, Felipe Alves Siqueira, João Pedro Mantovani Tarrega, João Vitor Pataca Beinotti, Augusto Sousa Nunes, Miguel de Mattos Gardini, Vinícius Adolfo Pereira da Silva, Nádia Félix Felipe da Silva, and André Carlos Ponce de Leon Ferreira de Carvalho · 2022
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Multi-label classification on remote-sensing images, 2022
Aditya Kumar Singh and B. Uma Shankar · 2022
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Volume-centred range bars: Novel interpretable representation of financial markets designed for machine learning applications, 2022
Artur Sokolovsky, Luca Arnaboldi, Jaume Bacardit, and Thomas Gross · 2022
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Meta-repository of screening mammography classifiers, 2022
Benjamin Stadnick, Jan Witowski, Vishwaesh Rajiv, Jakub Chłędowski, Farah E. Shamout, Kyunghyun Cho, and Krzysztof J. Geras · 2022
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Deep learning-based damage mapping with insar coherence time series
Oliver L. Stephenson, Tobias Köhne, Eric Zhan, Brent E. Cahill, Sang-Ho Yun, Zachary E. Ross, and Mark Simons · 2022
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Classic graph structural features outperform factorization-based graph embedding methods on community labeling
Andrew Stolman, Caleb Levy, C Seshadhri, and Aneesh Sharma · 2022
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Incremental knowledge tracing from multiple schools, 2022
Sujanya Suresh, Savitha Ramasamy, P. N. Suganthan, and Cheryl Sze Yin Wong · 2022
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A machine learning-based approach to detect threats in bio-cyber dna storage systems
Federico Tavella, Alberto Giaretta, Mauro Conti, and Sasitharan Balasubramaniam · 2022
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Real-time prediction of severe influenza epidemics using extreme value statistics
Maud Thomas and Holger Rootzén · 2022
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Differentially private synthetic medical data generation using convolutional gans
Amirsina Torfi, Edward A Fox, and Chandan K Reddy · 2022
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Drg-net: Interactive joint learning of multi-lesion segmentation and classification for diabetic retinopathy grading, 2022
Hasan Md Tusfiqur, Duy M. H. Nguyen, Mai T. N. Truong, Triet A. Nguyen, Binh T. Nguyen, Michael Barz, Hans-Juergen Profitlich, Ngoc T. T. Than, Ngan Le, Pengtao Xie, and Daniel Sonntag · 2022
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Open-set recognition: A good closed-set classifier is all you need
Sagar Vaze, Kai Han, Andrea Vedaldi, and Andrew Zisserman · 2022
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Momentum accelerates the convergence of stochastic auprc maximization
Guanghui Wang, Ming Yang, Lijun Zhang, and Tianbao Yang · 2022
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Rank the triplets: A ranking-based multiple instance learning framework for detecting hpv infection in head and neck cancers using routine h&e images, 2022
Ruoyu Wang, Syed Ali Khurram, Amina Asif, Lawrence Young, and Nasir Rajpoot · 2022
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Sana: cross-species prediction of gene ontology go annotations via topological network alignment
Siyue Wang, Giles R. S. Atkinson, and Wayne B. Hayes · 2022
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Detecting label errors in token classification data
Wei-Chen Wang and Jonas Mueller · 2022
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Exploring the algorithm-dependent generalization of auprc optimization with list stability
Peisong Wen, Qianqian Xu, Zhiyong Yang, Yuan He, and Qingming Huang · 2022
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A benchmark for unsupervised anomaly detection in multi-agent trajectories
Julian Wiederer, Julian Schmidt, Ulrich Kressel, Klaus Dietmayer, and Vasileios Belagiannis · 2022
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A pseudo label-wise attention network for automatic icd coding
Yifan Wu, Min Zeng, Ying Yu, Yaohang Li, and Min Li · 2022
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Multi-channel neural networks for predicting influenza a virus hosts and antigenic types
Yanhua Xu and Dominik Wojtczak · 2022
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The computational drug repositioning without negative sampling
Xinxing Yang, Genke Yang, and Jian Chu · 2022
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The neural metric factorization for computational drug repositioning
Xinxing Yang, Genke Yang, and Jian Chu · 2022
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Spldextratrees: robust machine learning approach for predicting kinase inhibitor resistance
Zi-Yi Yang, Zhao-Feng Ye, Yi-Jia Xiao, Chang-Yu Hsieh, and Sheng-Yu Zhang · 2022
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Dsr–a dual subspace re-projection network for surface anomaly detection
Vitjan Zavrtanik, Matej Kristan, and Danijel Skočaj · 2022
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M3care: Learning with missing modalities in multimodal healthcare data
Chaohe Zhang, Xu Chu, Liantao Ma, Yinghao Zhu, Yasha Wang, Jiangtao Wang, and Junfeng Zhao · 2022
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Multi-instance causal representation learning for instance label prediction and out-of-distribution generalization
Weijia Zhang, Xuanhui Zhang, hanwen deng, and Min-Ling Zhang · 2022
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Debiased-cam to mitigate image perturbations with faithful visual explanations of machine learning
Wencan Zhang, Mariella Dimiccoli, and Brian Y Lim · 2022
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Spot-the-difference self-supervised pre-training for anomaly detection and segmentation
Yang Zou, Jongheon Jeong, Latha Pemula, Dongqing Zhang, and Onkar Dabeer · 2022
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Nodecoder: a graph-based machine learning platform to predict active sites of modeled protein structures, 2023
Nasim Abdollahi, Seyed Ali Madani Tonekaboni, Jay Huang, Bo Wang, and Stephen MacKinnon · 2023
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Paying attention to astronomical transients: introducing the time-series transformer for photometric classification
Jr. Allam, Tarek and Jason D McEwen · 2023
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On the role of visual context in enriching music representations
Kleanthis Avramidis, Shanti Stewart, and Shrikanth Narayanan · 2023
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Molecular machine learning with conformer ensembles
Simon Axelrod and Rafael Gomez-Bombarelli · 2023
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Graph-based machine learning improves just-in-time defect prediction
Jonathan Bryan and Pablo Moriano · 2023
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Mri-based classification of idh mutation and 1p/19q codeletion status of gliomas using a 2.5 d hybrid multi-task convolutional neural network
Satrajit Chakrabarty, Pamela LaMontagne, Joshua Shimony, Daniel S Marcus, and Aristeidis Sotiras · 2023
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Structural attention-based recurrent variational autoencoder for highway vehicle anomaly detection
Neeloy Chakraborty, Aamir Hasan, Shuijing Liu, Tianchen Ji, Weihang Liang, D. Livingston McPherson, and Katherine Driggs-Campbell · 2023
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CHAD: Charlotte Anomaly Dataset
Armin Danesh Pazho, Ghazal Alinezhad Noghre, Babak Rahimi Ardabili, Christopher Neff, and Hamed Tabkhi · 2023
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Unraveling key elements underlying molecular property prediction: A systematic study, 2023
Jianyuan Deng, Zhibo Yang, Hehe Wang, Iwao Ojima, Dimitris Samaras, and Fusheng Wang · 2023
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Convolutional motif kernel networks, 2023
Jonas C. Ditz, Bernhard Reuter, and Nico Pfeifer · 2023
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Consistency pays off in science
Şirag Erkol, Satyaki Sikdar, Filippo Radicchi, and Santo Fortunato · 2023
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Bacadi: Bayesian causal discovery with unknown interventions
Alexander H"̈agele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Sch"̈olkopf, and Andreas Krause · 2023
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Towards reliable assessments of demographic disparities in multi-label image classifiers, 2023
Melissa Hall, Bobbie Chern, Laura Gustafson, Denisse Ventura, Harshad Kulkarni, Candace Ross, and Nicolas Usunier · 2023
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Inherent limits on topology-based link prediction, 2023
Justus I. Hibshman and Tim Weninger · 2023
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Heatmap-based out-of-distribution detection
Julia Hornauer and Vasileios Belagiannis · 2023
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From single-visit to multi-visit image-based models: single-visit models are enough to predict obstructive hydronephrosis
Stanley Bryan Z. Hua, Mandy Rickard, John Weaver, Alice Xiang, Daniel Alvarez, Kyla N. Velear, Kunj Sheth, Gregory E. Tasian, Armando J. Lorenzo, Anna Goldenberg, and Lauren Erdman · 2023
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Enhancing vulnerability prioritization: Data-driven exploit predictions with community-driven insights, 2023
Jay Jacobs, Sasha Romanosky, Octavian Suciu, Benjamin Edwards, and Armin Sarabi · 2023
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Detecting road obstacles by erasing them
Krzysztof Lis, Sina Honari, Pascal Fua, and Mathieu Salzmann · 2023
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Fine-grained selective similarity integration for drug–target interaction prediction
Bin Liu, Jin Wang, Kaiwei Sun, and Grigorios Tsoumakas · 2023
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Generalized video anomaly event detection: Systematic taxonomy and comparison of deep models, 2023
Yang Liu, Dingkang Yang, Yan Wang, Jing Liu, Jun Liu, Azzedine Boukerche, Peng Sun, and Liang Song · 2023
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Predicting tags for programming tasks by combining textual and source code data, 2023
Artyom Lobanov, Egor Bogomolov, Yaroslav Golubev, Mikhail Mirzayanov, and Timofey Bryksin · 2023
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Mortality prediction with adaptive feature importance recalibration for peritoneal dialysis patients
Liantao Ma, Chaohe Zhang, Junyi Gao, Xianfeng Jiao, Zhihao Yu, Yinghao Zhu, Tianlong Wang, Xinyu Ma, Yasha Wang, Wen Tang, et al · 2023
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Instruction clarification requests in multimodal collaborative dialogue games: Tasks, and an analysis of the CoDraw dataset
Brielen Madureira and David Schlangen · 2023
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Why you should stop using the roc curve, September 2023
Samuele Mazzanti · 2023
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Self-supervised pretraining and transfer learning enable flu and covid-19 predictions in small mobile sensing datasets
Mika A Merrill and Tim Althoff · 2023
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Limitations of receiver operating characteristic curve on imbalanced data: assist device mortality risk scores
Faezeh Movahedi, Rema Padman, and James F Antaki · 2023
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A meta-level analysis of online anomaly detectors
Antonios Ntroumpogiannis, Michail Giannoulis, Nikolaos Myrtakis, Vassilis Christophides, Eric Simon, and Ioannis Tsamardinos · 2023
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Deep weakly-supervised anomaly detection
Guansong Pang, Chunhua Shen, Huidong Jin, and Anton van den Hengel · 2023
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On (assessing) the fairness of risk score models
Eike Petersen, Melanie Ganz, Sune Holm, and Aasa Feragen · 2023
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Predicting municipalities in financial distress: a machine learning approach enhanced by domain expertise, 2023
Dario Piermarini, Antonio M. Sudoso, and Veronica Piccialli · 2023
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Deep learning for global wildfire forecasting, 2023
Ioannis Prapas, Akanksha Ahuja, Spyros Kondylatos, Ilektra Karasante, Eleanna Panagiotou, Lazaro Alonso, Charalampos Davalas, Dimitrios Michail, Nuno Carvalhais, and Ioannis Papoutsis · 2023
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Early prediction of the risk of icu mortality with deep federated learning
Korbinian Randl, Núria Lladós Armengol, Lena Mondrejevski, and Ioanna Miliou · 2023
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Identifying galaxy mergers in simulated ceers nircam images using random forests
Caitlin Rose, Jeyhan S Kartaltepe, Gregory F Snyder, Vicente Rodriguez-Gomez, LY Aaron Yung, Pablo Arrabal Haro, Micaela B Bagley, Antonello Calabró, Nikko J Cleri, MC Cooper, et al · 2023
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Teach me to play, gamer! imitative learning in computer games via linguistic description of complex phenomena and decision trees
Clemente Rubio-Manzano, Tomás Lermanda, Claudia Martínez-Araneda, Christian Vidal, and Alejandra Segura · 2023
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Predictive process model monitoring using recurrent neural networks, 2023
Johannes De Smedt and Jochen De Weerdt · 2023
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Prediction scoring of data-driven discoveries for reproducible research
Anna L Smith, Tian Zheng, and Andrew Gelman · 2023
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Uncertainty quantification for deep neural networks: An empirical comparison and usage guidelines
Michael Weiss and Paolo Tonella · 2023
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Cosmic-conn: A cosmic-ray detection deep-learning framework, data set, and toolkit
Chengyuan Xu, Curtis McCully, Boning Dong, D Andrew Howell, and Pradeep Sen · 2023
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Self-supervised learning for label sparsity in computational drug repositioning
Xinxing Yang, Genke Yang, and Jian Chu · 2023
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Towards a user privacy-aware mobile gaming app installation prediction model, 2023
Ido Zehori, Nevo Itzhak, Yuval Shahar, and Mia Dor Schiller · 2023
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