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Distribution shifts -- where the training distribution differs from the test distribution -- can substantially degrade the accuracy of machine learning (ML) systems deployed in the wild.
Limitations of pinned AUC for measuring unintended bias
D. Borkan, L. Dixon, J. Li, J. Sorensen, N. Thain, and L. Vasserman · 1903
Earlier work this paper cites.
Fair resource allocation in federated learning
T. Li, M. Sanjabi, A. Beirami, and V. Smith · 1905
Earlier work this paper cites.
Fairness Warnings and Fair-MAML: Learning Fairly with Minimal Data
Dylan Slack, Sorelle Friedler, and Emile Givental · 1908
Earlier work this paper cites.
Scaling out-of-distribution detection for real-world settings
D. Hendrycks, S. Basart, M. Mazeika, M. Mostajabi, J. Steinhardt, and D. Song · 1911
Earlier work this paper cites.
R. T. McCoy, J. Min, and T. Linzen · 1911
Earlier work this paper cites.
Precinct or prejudice? Understanding racial disparities in New York City’s stop-and-frisk policy
Sharad Goel, Justin M. Rao, and Ravi Shroff · 1932
Earlier work this paper cites.
Building a large annotated corpus of English: the Penn Treebank
M. P. Marcus, M. A. Marcinkiewicz, and B. Santorini · 1993
Earlier work this paper cites.
A method for improving classification reliability of multilayer perceptrons
L. P. Cordella, C. D. Stefano, F. Tortorella, and M. Vento · 1995
Earlier work this paper cites.
A large-scale experiment to assess protein structure prediction methods
J. Moult, J. T Pedersen, R. Judson, and K. Fidelis · 1995
Earlier work this paper cites.
The art and practice of structure-based drug design: a molecular modeling perspective
R. S. Bohacek, C. McMartin, and W. C. Guida · 1996
Earlier work this paper cites.
High-throughput screening for drug discovery
James R Broach, Jeremy Thorner, et al · 1996
Earlier work this paper cites.
Learning in the presence of concept drift and hidden contexts
G. Widmer and M. Kubat · 1996
Earlier work this paper cites.
Transcriptional activation by recruitment
Mark Ptashne and Alexander Gann · 1997
Earlier work this paper cites.
The MNIST database of handwritten digits
Y. LeCun, C. Cortes, and C. J. Burges · 1998
Earlier work this paper cites.
The myc/max/mad network and the transcriptional control of cell behavior
Carla Grandori, Shaun M Cowley, Leonard P James, and Robert N Eisenman · 2000
Earlier work this paper cites.
Improving predictive inference under covariate shift by weighting the log-likelihood function
H. Shimodaira · 2000
Earlier work this paper cites.
Rna interference and small interfering rnas
Thomas Tuschl · 2001
Earlier work this paper cites.
Adjusting the outputs of a classifier to new a priori probabilities: a simple procedure
M. Saerens, P. Latinne, and C. Decaestecker · 2002
Earlier work this paper cites.
A comparison of normalization methods for high density oligonucleotide array data based on variance and bias
Benjamin M Bolstad, Rafael A Irizarry, Magnus Åstrand, and Terence P. Speed · 2003
Earlier work this paper cites.
Xtreme: A massively multilingual multi-task benchmark for evaluating cross-lingual generalization
J. Hu, S. Ruder, A. Siddhant, G. Neubig, O. Firat, and M. Johnson · 2003
Earlier work this paper cites.
Exploring alternative measures of welfare in the absence of expenditure data
D. E. Sahn and D. Stifel · 2003
Earlier work this paper cites.
The iWildCam 2020 competition dataset
S. Beery, E. Cole, and A. Gjoka · 2004
Earlier work this paper cites.
Pretrained transformers improve out-of-distribution robustness
Dan Hendrycks, Xiaoyuan Liu, Eric Wallace, Adam Dziedzic, Rishabh Krishnan, and Dawn Song · 2004
Earlier work this paper cites.
Evidence for nucleosome depletion at active regulatory regions genome-wide
Cheol-Koo Lee, Yoichiro Shibata, Bhargavi Rao, Brian D Strahl, and Jason D Lieb · 2004
Earlier work this paper cites.
Virtual screening of chemical libraries
Brian K Shoichet · 2004
Earlier work this paper cites.
Open graph benchmark: Datasets for machine learning on graphs
W. Hu, M. Fey, M. Zitnik, Y. Dong, H. Ren, B. Liu, M. Catasta, and J. Leskovec · 2005
Earlier work this paper cites.
Analysis of representations for domain adaptation
S. Ben-David, J. Blitzer, K. Crammer, and F. Pereira · 2006
Earlier work this paper cites.
High-throughput rnai screening in cultured cells: a user’s guide
Christophe J Echeverri and Norbert Perrimon · 2006
Earlier work this paper cites.
Classifier technology and the illusion of progress
David J Hand · 2006
Earlier work this paper cites.
The many faces of robustness: A critical analysis of out-of-distribution generalization
D. Hendrycks, S. Basart, N. Mu, S. Kadavath, F. Wang, E. Dorundo, R. Desai, T. Zhu, S. Parajuli, M. Guo, D. Song, J. Steinhardt, and J. Gilmer · 2006
Earlier work this paper cites.
Rdkit: Open-source cheminformatics, 2006
Greg Landrum et al · 2006
Earlier work this paper cites.
Fully test-time adaptation by entropy minimization
D. Wang, E. Shelhamer, S. Liu, B. Olshausen, and T. Darrell · 2006
Earlier work this paper cites.
UCI Machine Learning Repository, 2007
Arthur Asuncion and David Newman · 2007
Earlier work this paper cites.
Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification
J. Blitzer, M. Dredze, and F. Pereira · 2007
Earlier work this paper cites.
An Analysis of the New York City Police Department’s “Stop-and-Frisk” Policy in the Context of Claims of Racial Bias
Andrew Gelman, Jeffrey Fagan, and Alex Kiss · 2007
Earlier work this paper cites.
Classification with a reject option using a hinge loss
P. L. Bartlett and M. H. Wegkamp · 2008
Earlier work this paper cites.
High-resolution mapping and characterization of open chromatin across the genome
Alan P Boyle, Sean Davis, Hennady P Shulha, Paul Meltzer, Elliott H Margulies, Zhiping Weng, Terrence S Furey, and Gregory E Crawford · 2008
Earlier work this paper cites.
Using remotely sensed night-time light as a proxy for poverty in Africa
A. Noor, V. Alegana, P. Gething, A. Tatem, and R. Snow · 2008
Earlier work this paper cites.
How program history can improve code completion
Romain Robbes and Michele Lanza · 2008
Earlier work this paper cites.
Learning from examples to improve code completion systems
Marcel Bruch, Martin Monperrus, and Mira Mezini · 2009
Earlier work this paper cites.
Domain adaptation problems: A DASVM classification technique and a circular validation strategy
L. Bruzzone and M. Marconcini · 2009
Earlier work this paper cites.
A global poverty map derived from satellite data
C. D. Elvidge, P. C. Sutton, T. Ghosh, B. T. Tuttle, K. E. Baugh, B. Bhaduri, and E. Bright · 2009
Earlier work this paper cites.
Histopathological image analysis: A review
M. N. Gurcan, L. E. Boucheron, A. Can, A. Madabhushi, N. M. Rajpoot, and B. Yener · 2009
Earlier work this paper cites.
A method for normalizing histology slides for quantitative analysis
M. Macenko, M. Niethammer, J. S. Marron, D. Borland, J. T. Woosley, X. Guan, C. Schmitt, and N. E. Thomas · 2009
Earlier work this paper cites.
Domain adaptation with multiple sources
Yishay Mansour, Mehryar Mohri, and Afshin Rostamizadeh · 2009
Earlier work this paper cites.
Dataset shift in machine learning
J. Quiñonero-Candela, M. Sugiyama, A. Schwaighofer, and N. D. Lawrence · 2009
Earlier work this paper cites.
The role of dna shape in protein-dna recognition
Remo Rohs, Sean M West, Alona Sosinsky, Peng Liu, Richard S Mann, and Barry Honig · 2009
Earlier work this paper cites.
The Creation and Validation of the Ohio Risk Assessment System (ORAS)
Edward J. Latessa, Richard Lemke, Matthew Makarios, and Paula Smith · 2010
Earlier work this paper cites.
Tackling the widespread and critical impact of batch effects in high-throughput data
J. T. Leek, R. B. Scharpf, H. C. Bravo, D. Simcha, B. Langmead, W. E. Johnson, D. Geman, K. Baggerly, and R. A. Irizarry · 2010
Earlier work this paper cites.
Using twinning to adapt programs to alternative apis
Marius Nita and David Notkin · 2010
Earlier work this paper cites.
Adapting visual category models to new domains
K. Saenko, B. Kulis, M. Fritz, and T. Darrell · 2010
Earlier work this paper cites.
Determining the specificity of protein-dna interactions
Gary D Stormo and Yue Zhao · 2010
Earlier work this paper cites.
Genome-wide prediction of transcription factor binding sites using an integrated model
Kyoung-Jae Won, Bing Ren, and Wei Wang · 2010
Earlier work this paper cites.
Bag-of-visual-words and spatial extensions for land-use classification
Y. Yang and S. Newsam · 2010
Earlier work this paper cites.
Systematic analysis of breast cancer morphology uncovers stromal features associated with survival
A. H. Beck, A. R. Sangoi, S. Leung, R. J. Marinelli, T. O. Nielsen, M. J. V. D. Vijver, R. B. West, M. V. D. Rijn, and D. Koller · 2011
Earlier work this paper cites.
Generalizing from several related classification tasks to a new unlabeled sample
G. Blanchard, G. Lee, and C. Scott · 2011
Earlier work this paper cites.
Underspecification presents challenges for credibility in modern machine learning
A. D’Amour, K. Heller, D. Moldovan, B. Adlam, B. Alipanahi, A. Beutel, C. Chen, J. Deaton, J. Eisenstein, M. D. Hoffman, et al · 2011
Earlier work this paper cites.
Assessing asset indices
D. Filmer and K. Scott · 2011
Earlier work this paper cites.
Principles of early drug discovery
James P Hughes, Stephen Rees, S Barrett Kalindjian, and Karen L Philpott · 2011
Earlier work this paper cites.
Impact of high-throughput screening in biomedical research
Ricardo Macarron, Martyn N Banks, Dejan Bojanic, David J Burns, Dragan A Cirovic, Tina Garyantes, Darren VS Green, Robert P Hertzberg, William P Janzen, Jeff W Paslay, et al · 2011
Earlier work this paper cites.
How were new medicines discovered?
David C Swinney and Jason Anthony · 2011
Earlier work this paper cites.
Unbiased look at dataset bias
A. Torralba and A. A. Efros · 2011
Earlier work this paper cites.
Reading digits in natural images with unsupervised feature learning
N. Yuval, W. Tao, C. Adam, B. Alessandro, W. Bo, and N. A. Y · 2011
Earlier work this paper cites.
An integrated encyclopedia of DNA elements in the human genome
E. P. Consortium et al · 2012
Earlier work this paper cites.
A review of recent advances in learner and skill modeling in intelligent learning environments
M. C. Desmarais and R. Baker · 2012
Earlier work this paper cites.
The protein-folding problem, 50 years on
K. A. Dill and J. L. MacCallum · 2012
Earlier work this paper cites.
Fairness through awareness
C. Dwork, M. Hardt, T. Pitassi, O. Reingold, and R. Zemel · 2012
Earlier work this paper cites.
The influence of race and ethnicity on the biology of cancer
B. E. Henderson, N. H. Lee, V. Seewaldt, and H. Shen · 2012
Earlier work this paper cites.
Chip-seq guidelines and practices of the encode and modencode consortia
Stephen G Landt, Georgi K Marinov, Anshul Kundaje, Pouya Kheradpour, Florencia Pauli, Serafim Batzoglou, Bradley E Bernstein, Peter Bickel, James B Brown, Philip Cayting, et al · 2012
Earlier work this paper cites.
Annotated high-throughput microscopy image sets for validation
Vebjorn Ljosa, Katherine L Sokolnicki, and Anne E Carpenter · 2012
Earlier work this paper cites.
The practical effect of batch on genomic prediction
Hilary S Parker and Jeffrey T Leek · 2012
Earlier work this paper cites.
Estimating escapement for a low-abundance steelhead population using dual-frequency identification sonar (didson)
Kerrie A Pipal, Jeremy J Notch, Sean A Hayes, and Peter B Adams · 2012
Earlier work this paper cites.
The accessible chromatin landscape of the human genome
Robert E Thurman, Eric Rynes, Richard Humbert, Jeff Vierstra, Matthew T Maurano, Eric Haugen, Nathan C Sheffield, Andrew B Stergachis, Hao Wang, Benjamin Vernot, et al · 2012
Earlier work this paper cites.
The tox21 robotic platform for the assessment of environmental chemicals–from vision to reality
M. S. Attene-Ramos, N. Miller, R. Huang, S. Michael, M. Itkin, R. J. Kavlock, C. P. Austin, P. Shinn, A. Simeonov, R. R. Tice, et al · 2013
Earlier work this paper cites.
Counterfactual reasoning and learning systems: The example of computational advertising
L. Bottou, J. Peters, J. Quiñonero-Candela, D. X. Charles, D. M. Chickering, E. Portugaly, D. Ray, P. Simard, and E. Snelson · 2013
Earlier work this paper cites.
Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, dna-binding proteins and nucleosome position
Jason D Buenrostro, Paul G Giresi, Lisa C Zaba, Howard Y Chang, and William J Greenleaf · 2013
Earlier work this paper cites.
Unbiased metric learning: On the utilization of multiple datasets and web images for softening bias
C. Fang, Y. Xu, and D. N. Rockmore · 2013
Earlier work this paper cites.
High-resolution global maps of 21st-century forest cover change
M. C. Hansen, P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend · 2013
Earlier work this paper cites.
Tuned models of peer assessment in moocs
C. Piech, J. Huang, Z. Chen, C. Do, A. Ng, and D. Koller · 2013
Earlier work this paper cites.
The cancer genome atlas pan-cancer analysis project
J. N. Weinstein, E. A. Collisson, G. B. Mills, K. R. M. Shaw, B. A. Ozenberger, K. Ellrott, I. Shmulevich, C. Sander, J. M. Stuart, C. G. A. R. Network, et al · 2013
Earlier work this paper cites.
Domain adaptation under target and conditional shift
K. Zhang, B. Schölkopf, K. Muandet, and Z. Wang · 2013
Earlier work this paper cites.
Targeting direct cash transfers to the extremely poor
B. Abelson, K. R. Varshney, and J. Sun · 2014
Earlier work this paper cites.
Perspective: Fifty years of density-functional theory in chemical physics
Axel D Becke · 2014
Earlier work this paper cites.
Comparative analysis of metazoan chromatin organization
J. W. Ho, Y. L. Jung, T. Liu, B. H. Alver, S. Lee, K. Ikegami, K. Sohn, A. Minoda, M. Y. Tolstorukov, A. Appert, et al · 2014
Earlier work this paper cites.
Scaling short-answer grading by combining peer assessment with algorithmic scoring
C. E. Kulkarni, R. Socher, M. S. Bernstein, and S. R. Klemmer · 2014
Earlier work this paper cites.
Social analytics: Learning fuzzy product ontologies for aspect-oriented sentiment analysis
R. Y. Lau, C. Li, and S. S. Liao · 2014
Earlier work this paper cites.
When “the state of the art” is counting words
L. Perelman · 2014
Earlier work this paper cites.
A review of novelty detection
M. A. Pimentel, D. A. Clifton, L. Clifton, and L. Tarassenko · 2014
Earlier work this paper cites.
Code completion with statistical language models
Veselin Raychev, Martin Vechev, and Eran Yahav · 2014
Earlier work this paper cites.
Lectures on stochastic programming: modeling and theory
Alexander Shapiro, Darinka Dentcheva, and Andrzej Ruszczyński · 2014
Earlier work this paper cites.
State-of-the-art automated essay scoring: Competition, results, and future directions from a united states demonstration
M. D. Shermis · 2014
Earlier work this paper cites.
Batch effect confounding leads to strong bias in performance estimates obtained by cross-validation
Charlotte Soneson, Sarah Gerster, and Mauro Delorenzi · 2014
Earlier work this paper cites.
Deep domain confusion: Maximizing for domain invariance
Eric Tzeng, Judy Hoffman, Ning Zhang, Kate Saenko, and Trevor Darrell · 2014
Earlier work this paper cites.
Exploiting social network structure for person-to-person sentiment analysis
R. West, H. S. Paskov, J. Leskovec, and C. Potts · 2014
Earlier work this paper cites.
High-throughput screening of a crispr/cas9 library for functional genomics in human cells
Yuexin Zhou, Shiyou Zhu, Changzu Cai, Pengfei Yuan, Chunmei Li, Yanyi Huang, and Wensheng Wei · 2014
Earlier work this paper cites.
Exploring machine learning methods to automatically identify students in need of assistance
A. Ahadi, R. Lister, H. Haapala, and A. Vihavainen · 2015
Earlier work this paper cites.
Predicting the sequence specificities of dna-and rna-binding proteins by deep learning
Babak Alipanahi, Andrew Delong, Matthew T Weirauch, and Brendan J Frey · 2015
Earlier work this paper cites.
Suggesting accurate method and class names
Miltiadis Allamanis, Earl T Barr, Christian Bird, and Charles Sutton · 2015
Earlier work this paper cites.
Improved concept drift handling in surgery prediction and other applications
A. A. Beyene, T. Welemariam, M. Persson, and N. Lavesson · 2015
Earlier work this paper cites.
Predicting poverty and wealth from mobile phone metadata
J. Blumenstock, G. Cadamuro, and R. On · 2015
Earlier work this paper cites.
Microscopy-based high-content screening
Michael Boutros, Florian Heigwer, and Christina Laufer · 2015
Earlier work this paper cites.
Data for development: A needs assessment for SDG monitoring and statistical capacity development
J. Espey, E. Swanson, S. Badiee, Z. Chistensen, A. Fischer, M. Levy, G. Yetman, A. de Sherbinin, R. Chen, Y. Qiu, G. Greenwell, T. Klein, , J. Jutting, M. Jerven, G. Cameron, A. M. A. Rivera, V. C. Arias, , S. L. Mills, and A. Motivans · 2015
Earlier work this paper cites.
Cacheca: A cache language model based code suggestion tool
Christine Franks, Zhaopeng Tu, Premkumar Devanbu, and Vincent Hellendoorn · 2015
Earlier work this paper cites.
Unsupervised domain adaptation by backpropagation
Y. Ganin and V. Lempitsky · 2015
Earlier work this paper cites.
Explaining and harnessing adversarial examples
I. J. Goodfellow, J. Shlens, and C. Szegedy · 2015
Earlier work this paper cites.
Challenges of studying and processing dialects in social media
A. K. Jørgensen, D. Hovy, and A. Søgaard · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2015
Earlier work this paper cites.
Peer and self assessment in massive online classes
C. Kulkarni, P. W. Koh, H. Huy, D. Chia, K. Papadopoulos, J. Cheng, D. Koller, and S. R. Klemmer · 2015
Earlier work this paper cites.
Integrative analysis of 111 reference human epigenomes
A. Kundaje, W. Meuleman, J. Ernst, M. Bilenky, A. Yen, A. Heravi-Moussavi, P. Kheradpour, Z. Zhang, J. Wang, M. J. Ziller, et al · 2015
Earlier work this paper cites.
Machine learning applications in genetics and genomics
M. W. Libbrecht and W. S. Noble · 2015
Earlier work this paper cites.
Learning transferable features with deep adaptation networks
M. Long, Y. Cao, J. Wang, and M. Jordan · 2015
Earlier work this paper cites.
Maximin effects in inhomogeneous large-scale data
Nicolai Meinshausen and Peter Bühlmann · 2015
Earlier work this paper cites.
Graph-based statistical language model for code
Anh Tuan Nguyen and Tien N Nguyen · 2015
Earlier work this paper cites.
Librispeech: an ASR corpus based on public domain audio books
V. Panayotov, G. Chen, D. Povey, and S. Khudanpur · 2015
Earlier work this paper cites.
Intelligent code completion with bayesian networks
Sebastian Proksch, Johannes Lerch, and Mira Mezini · 2015
Earlier work this paper cites.
Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Earlier work this paper cites.
Zinc 15 – ligand discovery for everyone
Teague Sterling and John J. Irwin · 2015
Earlier work this paper cites.
Speech accent archive
S. Weinberger · 2015
Earlier work this paper cites.
Predicting effects of noncoding variants with deep learning–based sequence model
J. Zhou and O. G. Troyanskaya · 2015
Earlier work this paper cites.
Demographic dialectal variation in social media: A case study of African-American English
S. L. Blodgett, L. Green, and B. O’Connor · 2016
Earlier work this paper cites.
Cell painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes
Mark-Anthony Bray, Shantanu Singh, Han Han, Chadwick T Davis, Blake Borgeson, Cathy Hartland, Maria Kost-Alimova, Sigrun M Gustafsdottir, Christopher C Gibson, and Anne E Carpenter · 2016
Earlier work this paper cites.
Sources of variation in under-5 mortality across sub-Saharan Africa: a spatial analysis
M. Burke, S. Heft-Neal, and E. Bendavid · 2016
Earlier work this paper cites.
A computer program used for bail and sentencing decisions was labeled biased against blacks. It’s actually not that clear
Sam Corbett-Davies, Emma Pierson, Avi Feller, and Sharad Goel · 2016
Earlier work this paper cites.
The genetics of transcription factor dna binding variation
Bart Deplancke, Daniel Alpern, and Vincent Gardeux · 2016
Earlier work this paper cites.
Spacenet
N. DigitalGlobe and C. Works · 2016
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Dropout as a Bayesian approximation: Representing model uncertainty in deep learning
Y. Gal and Z. Ghahramani · 2016
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Domain-adversarial training of neural networks
Y. Ganin, E. Ustinova, H. Ajakan, P. Germain, H. Larochelle, F. Laviolette, M. March, and V. Lempitsky · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Earlier work this paper cites.
The social impact of natural language processing
D. Hovy and S. L. Spruit · 2016
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Combining satellite imagery and machine learning to predict poverty
N. Jean, M. Burke, M. Xie, W. M. Davis, D. B. Lobell, and S. Ermon · 2016
Earlier work this paper cites.
Mimic-iii, a freely accessible critical care database
Alistair EW Johnson, Tom J Pollard, Lu Shen, H Lehman Li-Wei, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony Celi, and Roger G Mark · 2016
Earlier work this paper cites.
Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks
D. R. Kelley, J. Snoek, and J. L. Rinn · 2016
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How we analyzed the compas recidivism algorithm
Jeff Larson, Surya Mattu, Lauren Kirchner, and Julia Angwin · 2016
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To predict and serve?
Kristian Lum and William Isaac · 2016
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Methods that remove batch effects while retaining group differences may lead to exaggerated confidence in downstream analyses
Vegard Nygaard, Einar Andreas Rødland, and Eivind Hovig · 2016
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The Times is partnering with Jigsaw to expand comment capabilities
NYTimes · 2016
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Causal inference by using invariant prediction: identification and confidence intervals
Jonas Peters, Peter Bühlmann, and Nicolai Meinshausen · 2016
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Evaluating the evaluations of code recommender systems: A reality check
Sebastian Proksch, Sven Amann, Sarah Nadi, and Mira Mezini · 2016
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Probabilistic model for code with decision trees
Veselin Raychev, Pavol Bielik, and Martin Vechev · 2016
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Playing for data: Ground truth from computer games
Selectivenet: A deep neural network with an integrated reject option
Y. Geifman and R. El-Yaniv · 2019
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Are we modeling the task or the annotator? an investigation of annotator bias in natural language understanding datasets
M. Geva, Y. Goldberg, and J. Berant · 2019
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Considerations for strategic use of high-throughput transcriptomics chemical screening data in regulatory decisions
Joshua Harrill, Imran Shah, R. Woodrow Setzer, Derik Haggard, Scott Auerbach, Richard Judson, and Russell S. Thomas · 2019
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When code completion fails: A case study on real-world completions
Vincent J Hellendoorn, Sebastian Proksch, Harald C Gall, and Alberto Bacchelli · 2019
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Benchmarking neural network robustness to common corruptions and perturbations
D. Hendrycks and T. Dietterich · 2019
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alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
S. R. Richter, V. Vineet, S. Roth, and V. Koltun · 2016
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The SYNTHIA dataset: A large collection of synthetic images for semantic segmentation of urban scenes
G. Ros, L. Sellart, J. Materzynska, D. Vazquez, and A. M. Lopez · 2016
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Unmanned aerial vehicles for high-throughput phenotyping and agronomic research
Yeyin Shi, J. Alex Thomasson, Seth C. Murray, N. Ace Pugh, William L. Rooney, Sanaz Shafian, Nithya Rajan, Gregory Rouze, Cristine L. S. Morgan, Haly L. Neely, Aman Rana, Muthu V. Bagavathiannan, James Henrickson, Ezekiel Bowden, John Valasek, Jeff Olsenholler, Michael P. Bishop, Ryan Sheridan, Eric B. Putman, Sorin Popescu, Travis Burks, Dale Cope, Amir Ibrahim, Billy F. McCutchen, David D. Baltensperger, Robert V. Avant, Jr, Misty Vidrine, and Chenghai Yang · 2016
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Deep CORAL: Correlation alignment for deep domain adaptation
B. Sun and K. Saenko · 2016
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Return of frustratingly easy domain adaptation
B. Sun, J. Feng, and K. Saenko · 2016
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A neural approach to automated essay scoring
K. Taghipour and H. T. Ng · 2016
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Mitosis counting in breast cancer: Object-level interobserver agreement and comparison to an automatic method
M. Veta, P. J. V. Diest, M. Jiwa, S. Al-Janabi, and J. P. Pluim · 2016
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Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit, Miltiadis Allamanis, and Marc Brockschmidt · 2019
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Predicting splicing from primary sequence with deep learning
K. Jaganathan, S. K. Panagiotopoulou, J. F. McRae, S. F. Darbandi, D. Knowles, Y. I. Li, J. A. Kosmicki, J. Arbelaez, W. Cui, G. B. Schwartz, et al · 2019
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Learning the difference that makes a difference with counterfactually-augmented data
D. Kaushik, E. Hovy, and Z. Lipton · 2019
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Accurate prediction of cell type-specific transcription factor binding
J. Keilwagen, S. Posch, and J. Grau · 2019
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Spoc: Search-based pseudocode to code
Sumith Kulal, Panupong Pasupat, Kartik Chandra, Mina Lee, Oded Padon, Alex Aiken, and Percy S Liang · 2019
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Data augmentation for leaf segmentation and counting tasks in rosette plants
Dmitry Kuznichov, Alon Zvirin, Yaron Honen, and Ron Kimmel · 2019
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Leopard: fast decoding cell type-specific transcription factor binding landscape at single-nucleotide resolution
H. Li and Y. Guan · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
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Measures of fairness for New York City’s Supervised Release Risk Assessment Tool
Kristian Lum and Tarak Shah · 2019
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Ultra-large library docking for discovering new chemotypes
J. Lyu, S. Wang, T. E. Balius, I. Singh, A. Levit, Y. S. Moroz, M. J. O’Meara, T. Che, E. Algaa, K. Tolmachova, et al · 2019
Later among the works it cites.
Ear density estimation from high resolution rgb imagery using deep learning technique
Simon Madec, Xiuliang Jin, Hao Lu, Benoit De Solan, Shouyang Liu, Florent Duyme, Emmanuelle Heritier, and Frederic Baret · 2019
Later among the works it cites.
A survey on bias and fairness in machine learning
Ninareh Mehrabi, Fred Morstatter, Nripsuta Saxena, Kristina Lerman, and Aram Galstyan · 2019
Later among the works it cites.
B. Nestor, M. McDermott, W. Boag, G. Berner, T. Naumann, M. C. Hughes, A. Goldenberg, and M. Ghassemi · 2019
Later among the works it cites.
Justifying recommendations using distantly-labeled reviews and fine-grained aspects
J. Ni, J. Li, and J. McAuley · 2019
Later among the works it cites.
A deep active learning system for species identification and counting in camera trap images
Mohammad Sadegh Norouzzadeh, Dan Morris, Sara Beery, Neel Joshi, Nebojsa Jojic, and Jeff Clune · 2019
Later among the works it cites.
Dissecting racial bias in an algorithm used to manage the health of populations
Z. Obermeyer, B. Powers, C. Vogeli, and S. Mullainathan · 2019
Later among the works it cites.
Distributionally robust language modeling
Y. Oren, S. Sagawa, T. Hashimoto, and P. Liang · 2019
Later among the works it cites.
Can you trust your model’s uncertainty? evaluating predictive uncertainty under dataset shift
Y. Ovadia, E. Fertig, J. Ren, Z. Nado, D. Sculley, S. Nowozin, J. V. Dillon, B. Lakshminarayanan, and J. Snoek · 2019
Later among the works it cites.
Moment matching for multi-source domain adaptation
X. Peng, Q. Bai, X. Xia, Z. Huang, K. Saenko, and B. Wang · 2019
Later among the works it cites.
Privacy in the age of medical big data
W Nicholson Price and I Glenn Cohen · 2019
Later among the works it cites.
Factornet: a deep learning framework for predicting cell type specific transcription factor binding from nucleotide-resolution sequential data
D. Quang and X. Xie · 2019
Later among the works it cites.
Overton: A data system for monitoring and improving machine-learned products
C. Ré, F. Niu, P. Gudipati, and C. Srisuwananukorn · 2019
Later among the works it cites.
Do ImageNet classifiers generalize to ImageNet?
B. Recht, R. Roelofs, L. Schmidt, and V. Shankar · 2019
Later among the works it cites.
Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf · 2019
Later among the works it cites.
The risk of racial bias in hate speech detection
M. Sap, D. Card, S. Gabriel, Y. Choi, and N. A. Smith · 2019
Later among the works it cites.
Do image classifiers generalize across time?
V. Shankar, A. Dave, R. Roelofs, D. Ramanan, B. Recht, and L. Schmidt · 2019
Later among the works it cites.
Not using the car to see the sidewalk–quantifying and controlling the effects of context in classification and segmentation
Rakshith Shetty, Bernt Schiele, and Mario Fritz · 2019
Later among the works it cites.
Synthetic datasets for neural program synthesis
Richard Shin, Neel Kant, Kavi Gupta, Christopher Bender, Brandon Trabucco, Rishabh Singh, and Dawn Song · 2019
Later among the works it cites.
Automatic acoustic detection of birds through deep learning: the first bird audio detection challenge
Dan Stowell, Michael D Wood, Hanna Pamuła, Yannis Stylianou, and Hervé Glotin · 2019
Later among the works it cites.
Pythia: ai-assisted code completion system
Alexey Svyatkovskiy, Ying Zhao, Shengyu Fu, and Neel Sundaresan · 2019
Later among the works it cites.
Machine learning to classify animal species in camera trap images: Applications in ecology
Michael A Tabak, Mohammad S Norouzzadeh, David W Wolfson, Steven J Sweeney, Kurt C VerCauteren, Nathan P Snow, Joseph M Halseth, Paul A Di Salvo, Jesse S Lewis, Michael D White, et al · 2019
Later among the works it cites.
Rxrx1: An image set for cellular morphological variation across many experimental batches
J. Taylor, B. Earnshaw, B. Mabey, M. Victors, and J. Yosinski · 2019
Later among the works it cites.
Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology
D. Tellez, G. Litjens, P. Bándi, W. Bulten, J. Bokhorst, F. Ciompi, and J. van der Laak · 2019
Later among the works it cites.
How convolutional neural networks diagnose plant disease
Yosuke Toda and Fumio Okura · 2019
Later among the works it cites.
Neural program repair by jointly learning to localize and repair
Marko Vasic, Aditya Kanade, Petros Maniatis, David Bieber, and Rishabh Singh · 2019
Later among the works it cites.
Predicting breast tumor proliferation from whole-slide images: the tupac16 challenge
M. Veta, Y. J. Heng, N. Stathonikos, B. E. Bejnordi, F. Beca, T. Wollmann, K. Rohr, M. A. Shah, D. Wang, M. Rousson, et al · 2019
Later among the works it cites.
Predictive inequity in object detection
Benjamin Wilson, Judy Hoffman, and Jamie Morgenstern · 2019
Later among the works it cites.
HuggingFace’s transformers: State-of-the-art natural language processing
T. Wolf, L. Debut, V. Sanh, J. Chaumond, C. Delangue, A. Moi, P. Cistac, T. Rault, R. Louf, M. Funtowicz, and J. Brew · 2019
Later among the works it cites.
Tasselnetv2: in-field counting of wheat spikes with context-augmented local regression networks
Haipeng Xiong, Zhiguo Cao, Hao Lu, Simon Madec, Liang Liu, and Chunhua Shen · 2019
Later among the works it cites.
Data efficient reinforcement learning for legged robots
Y. Yang, K. Caluwaerts, A. Iscen, T. Zhang, J. Tan, and V. Sindhwani · 2019
Later among the works it cites.
Paws: Paraphrase adversaries from word scrambling
Y. Zhang, J. Baldridge, and L. He · 2019
Later among the works it cites.
Fairness and robustness in invariant learning: A case study in toxicity classification
R. Adragna, E. Creager, D. Madras, and R. Zemel · 2020
Closest in time.
Wildlife insights: A platform to maximize the potential of camera trap and other passive sensor wildlife data for the planet
Jorge A Ahumada, Eric Fegraus, Tanya Birch, Nicole Flores, Roland Kays, Timothy G O’Brien, Jonathan Palmer, Stephanie Schuttler, Jennifer Y Zhao, Walter Jetz, Margaret Kinnaird, Sayali Kulkarni, Arnaud Lyet, David Thau, Michelle Duong, Ruth Oliver, and Anthony Dancer · 2020
Closest in time.
Maximum likelihood with bias-corrected calibration is hard-to-beat at label shift adaptation
A. Alexandari, A. Kundaje, and A. Shrikumar · 2020
Closest in time.
Common voice: A massively-multilingual speech corpus
R. Ardila, M. Branson, K. Davis, M. Kohler, J. Meyer, M. Henretty, R. Morais, L. Saunders, F. Tyers, and G. Weber · 2020
Closest in time.
The Inclusive Images competition
J. Atwood, Y. Halpern, P. Baljekar, E. Breck, D. Sculley, P. Ostyakov, S. I. Nikolenko, I. Ivanov, R. Solovyev, W. Wang, et al · 2020
Closest in time.
Unsupervised domain adaptation for plant organ counting
Tewodros W Ayalew, Jordan R Ubbens, and Ian Stavness · 2020
Closest in time.
Encode-dream in vivo transcription factor binding site prediction challenge
Akshay Balsubramani, Nathan Boley, Jin Wook Lee, Rani K. Powers, Bruce Hoff, Thomas Yu, Tim Jeske, Stephen Friend, Thea Norman, Gustavo Stolovitzky, Robert Kueffner, Laura M. Heiser, James C. Costello, and Anshul Kundaje · 2020
Closest in time.
A-levels and GCSEs: How did the exam algorithm work?
BBC · 2020
Closest in time.
A human-centered evaluation of a deep learning system deployed in clinics for the detection of diabetic retinopathy
E. Beede, E. Baylor, F. Hersch, A. Iurchenko, L. Wilcox, P. Ruamviboonsuk, and L. M. Vardoulakis · 2020
Closest in time.
Evaluating progress on machine learning for longitudinal electronic healthcare data
D. Bellamy, L. Celi, and A. L. Beam · 2020
Closest in time.
Autonomous navigation of stratospheric balloons using reinforcement learning
M. G. Bellemare, S. Candido, P. S. Castro, J. Gong, M. C. Machado, S. Moitra, S. S. Ponda, and Z. Wang · 2020
Closest in time.
When algorithms give real students imaginary grades
M. Broussard · 2020
Closest in time.
Heteroskedastic and imbalanced deep learning with adaptive regularization
K. Cao, Y. Chen, J. Lu, N. Arechiga, A. Gaidon, and T. Ma · 2020
Closest in time.
The Open Catalyst 2020 (oc20) dataset and community challenges
L. Chanussot, A. Das, S. Goyal, T. Lavril, M. Shuaibi, M. Riviere, K. Tran, J. Heras-Domingo, C. Ho, W. Hu, A. Palizhati, A. Sriram, B. Wood, J. Yoon, D. Parikh, C. L. Zitnick, and Z. Ulissi · 2020
Closest in time.
Ethical machine learning in health care
I. Y. Chen, E. Pierson, S. Rose, S. Joshi, K. Ferryman, and M. Ghassemi · 2020
Closest in time.
Tydi qa: A benchmark for information-seeking question answering in typologically diverse languages
J. H. Clark, E. Choi, M. Collins, D. Garrette, T. Kwiatkowski, V. Nikolaev, and J. Palomaki · 2020
Closest in time.
The GTEx Consortium atlas of genetic regulatory effects across human tissues
G. Consortium et al · 2020
Closest in time.
Robustbench: a standardized adversarial robustness benchmark
F. Croce, M. Andriushchenko, V. Sehwag, N. Flammarion, M. Chiang, P. Mittal, and M. Hein · 2020
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Listening and watching: Do camera traps or acoustic sensors more efficiently detect wild chimpanzees in an open habitat?
Anne-Sophie Crunchant, David Borchers, Hjalmar Kühl, and Alex Piel · 2020
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Functional immune mapping with deep-learning enabled phenomics applied to immunomodulatory and COVID-19 drug discovery
M. F. Cuccarese, B. A. Earnshaw, K. Heiser, B. Fogelson, C. T. Davis, P. F. McLean, H. B. Gordon, K. Skelly, F. L. Weathersby, V. Rodic, et al · 2020
Closest in time.
Fairness is not static: deeper understanding of long term fairness via simulation studies
A. D’Amour, H. Srinivasan, J. Atwood, P. Baljekar, D. Sculley, and Y. Halpern · 2020
Closest in time.
Global wheat head detection (gwhd) dataset: a large and diverse dataset of high-resolution rgb-labelled images to develop and benchmark wheat head detection methods
Etienne David, Simon Madec, Pouria Sadeghi-Tehran, Helge Aasen, Bangyou Zheng, Shouyang Liu, Norbert Kirchgessner, Goro Ishikawa, Koichi Nagasawa, Minhajul A Badhon, Curtis Pozniak, Benoit de Solan, Andreas Hund, Scott C. Chapman, Frederic Baret, Ian Stavness, and Wei Guo · 2020
Closest in time.
AI for radiographic COVID-19 detection selects shortcuts over signal
A. J. DeGrave, J. D. Janizek, and S. Lee · 2020
Closest in time.
On robustness and transferability of convolutional neural networks
J. Djolonga, J. Yung, M. Tschannen, R. Romijnders, L. Beyer, A. Kolesnikov, J. Puigcerver, M. Minderer, A. D’Amour, D. Moldovan, et al · 2020
Closest in time.
Distributionally robust losses for latent covariate mixtures
John Duchi, Tatsunori Hashimoto, and Hongseok Namkoong · 2020
Closest in time.
The myth of generalisability in clinical research and machine learning in health care
J. Futoma, M. Simons, T. Panch, F. Doshi-Velez, and L. A. Celi · 2020
Closest in time.
A unified view of label shift estimation
S. Garg, Y. Wu, S. Balakrishnan, and Z. C. Lipton · 2020
Closest in time.
Shortcut learning in deep neural networks
R. Geirhos, J. Jacobsen, C. Michaelis, R. Zemel, W. Brendel, M. Bethge, and F. A. Wichmann · 2020
Closest in time.
Model patching: Closing the subgroup performance gap with data augmentation
K. Goel, A. Gu, Y. Li, and C. Ré · 2020
Closest in time.
Unsupervised domain adaptation for transferring plant classification systems to new field environments, crops, and robots
Dario Gogoll, Philipp Lottes, Jan Weyler, Nik Petrinic, and Cyrill Stachniss · 2020
Closest in time.
Living Planet Report 2020 - Bending the curve of biodiversity loss
M Grooten, T Peterson, and R.E.A Almond · 2020
Closest in time.
In search of lost domain generalization
I. Gulrajani and D. Lopez-Paz · 2020
Closest in time.
Fortifying toxic speech detectors against veiled toxicity
X. Han and Y. Tsvetkov · 2020
Closest in time.
Towards non-IID image classification: A dataset and baselines
Y. He, Z. Shen, and P. Cui · 2020
Closest in time.
Enforcing predictive invariance across structured biomedical domains
W. Jin, R. Barzilay, and T. Jaakkola · 2020
Closest in time.
High accuracy protein structure prediction using deep learning
J. Jumper, R. Evans, A. Pritzel, T. Green, M. Figurnov, K. Tunyasuvunakool, O. Ronneberger, R. Bates, A. Žídek, A. Bridgland, C. Meyer, S. A A Kohl, A. Potapenko, A. J Ballard, A. Cowie, B. Romera-Paredes, S. Nikolov, R. Jain, J. Adler, T. Back, S. Petersen, D. Reiman, M. Steinegger, M. Pacholska, D. Silver, O. Vinyals, A. W Senior, K. Kavukcuoglu, P. Kohli, and D. Hassabis · 2020
Closest in time.
The limits of human predictions of recidivism
Jongbin Jung, Sharad Goel, Jennifer Skeem, et al · 2020
Closest in time.
BADGR: An autonomous self-supervised learning-based navigation system
G. Kahn, P. Abbeel, and S. Levine · 2020
Closest in time.
Selective question answering under domain shift
A. Kamath, R. Jia, and P. Liang · 2020
Closest in time.
Cogs: A compositional generalization challenge based on semantic interpretation
N. Kim and T. Linzen · 2020
Closest in time.
Racial disparities in automated speech recognition
A. Koenecke, A. Nam, E. Lake, J. Nudell, M. Quartey, Z. Mengesha, C. Toups, J. R. Rickford, D. Jurafsky, and S. Goel · 2020
Closest in time.
Concept bottleneck models
P. W. Koh, T. Nguyen, Y. S. Tang, S. Mussmann, E. Pierson, B. Kim, and P. Liang · 2020
Closest in time.
Empirical frequentist coverage of deep learning uncertainty quantification procedures
B. Kompa, J. Snoek, and A. Beam · 2020
Closest in time.
Understanding self-training for gradual domain adaptation
A. Kumar, T. Ma, and P. Liang · 2020
Closest in time.
Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis
Agostina J Larrazabal, Nicolás Nieto, Victoria Peterson, Diego H Milone, and Enzo Ferrante · 2020
Closest in time.
Machine learning on DNA-encoded libraries: A new paradigm for hit finding
K. McCloskey, E. A. Sigel, S. Kearnes, L. Xue, X. Tian, D. Moccia, D. Gikunju, S. Bazzaz, B. Chan, M. A. Clark, et al · 2020
Closest in time.
International evaluation of an AI system for breast cancer screening
S. M. McKinney, M. Sieniek, V. Godbole, J. Godwin, N. Antropova, H. Ashrafian, T. Back, M. Chesus, G. C. Corrado, A. Darzi, et al · 2020
Closest in time.
The effect of natural distribution shift on question answering models
J. Miller, K. Krauth, B. Recht, and L. Schmidt · 2020
Closest in time.
Expanded encyclopaedias of DNA elements in the human and mouse genomes
J. E. Moore, M. J. Purcaro, H. E. Pratt, C. B. Epstein, N. Shoresh, J. Adrian, T. Kawli, C. A. Davis, A. Dobin, R. Kaul, et al · 2020
Closest in time.
Learning from failure: Training debiased classifier from biased classifier
Junhyun Nam, Hyuntak Cha, Sungsoo Ahn, Jaeho Lee, and Jinwoo Shin · 2020
Closest in time.
Participatory research for low-resourced machine translation: A case study in African languages
W. Nekoto, V. Marivate, T. Matsila, T. Fasubaa, T. Kolawole, T. Fagbohungbe, S. O. Akinola, S. H. Muhammad, S. Kabongo, S. Osei, S. Freshia, R. A. Niyongabo, R. Macharm, P. Ogayo, O. Ahia, M. Meressa, M. Adeyemi, M. Mokgesi-Selinga, L. Okegbemi, L. J. Martinus, K. Tajudeen, K. Degila, K. Ogueji, K. Siminyu, J. Kreutzer, J. Webster, J. T. Ali, J. Abbott, I. Orife, I. Ezeani, I. A. Dangana, H. Kamper, H. Elsahar, G. Duru, G. Kioko, E. Murhabazi, E. van Biljon, D. Whitenack, C. Onyefuluchi, C. Emezue, B. Dossou, B. Sibanda, B. I. Bassey, A. Olabiyi, A. Ramkilowan, A. Öktem, A. Akinfaderin, and A. Bashir · 2020
Closest in time.
Fairrec: Two-sided fairness for personalized recommendations in two-sided platforms
G. K. Patro, A. Biswas, N. Ganguly, K. P. Gummadi, and A. Chakraborty · 2020
Closest in time.
Learning agile robotic locomotion skills by imitating animals
X. Peng, E. Coumans, T. Zhang, T. Lee, J. Tan, and S. Levine · 2020
Closest in time.
N. A. Phillips, P. Rajpurkar, M. Sabini, R. Krishnan, S. Zhou, A. Pareek, N. M. Phu, C. Wang, A. Y. Ng, and M. P. Lungren · 2020
Closest in time.
Practical considerations for active machine learning in drug discovery
D. Reker · 2020
Closest in time.
Breeder friendly phenotyping
Matthew Reynolds, Scott Chapman, Leonardo Crespo-Herrera, Gemma Molero, Suchismita Mondal, Diego NL Pequeno, Francisco Pinto, Francisco J Pinera-Chavez, Jesse Poland, Carolina Rivera-Amado, et al · 2020
Closest in time.
Beyond accuracy: Behavioral testing of NLP models with CheckList
M. T. Ribeiro, T. Wu, C. Guestrin, and S. Singh · 2020
Closest in time.
Post-estimation smoothing: A simple baseline for learning with side information
E. Rolf, M. I. Jordan, and B. Recht · 2020
Closest in time.
Breeds: Benchmarks for subpopulation shift
S. Santurkar, D. Tsipras, and A. Madry · 2020
Closest in time.
Counting fish and dolphins in sonar images using deep learning
Stefan Schneider and Alex Zhuang · 2020
Closest in time.
Chexclusion: Fairness gaps in deep chest X-ray classifiers
L. Seyyed-Kalantari, G. Liu, M. McDermott, and M. Ghassemi · 2020
Closest in time.
Deep neural networks for automated detection of marine mammal species
Yu Shiu, KJ Palmer, Marie A Roch, Erica Fleishman, Xiaobai Liu, Eva-Marie Nosal, Tyler Helble, Danielle Cholewiak, Douglas Gillespie, and Holger Klinck · 2020
Closest in time.
No subclass left behind: Fine-grained robustness in coarse-grained classification problems
N. Sohoni, J. Dunnmon, G. Angus, A. Gu, and C. Ré · 2020
Closest in time.
Sequence and chromatin determinants of transcription factor binding and the establishment of cell type-specific binding patterns
D. Srivastava and S. Mahony · 2020
Closest in time.
Robustness to Spurious Correlations via Human Annotations
Megha Srivastava, Tatsunori Hashimoto, and Percy Liang · 2020
Closest in time.
Evaluating model robustness to dataset shift
A. Subbaswamy, R. Adams, and S. Saria · 2020
Closest in time.
Correcting nuisance variation using wasserstein distance
Gil Tabak, Minjie Fan, Samuel Yang, Stephan Hoyer, and Geoffrey Davis · 2020
Closest in time.
Measuring robustness to natural distribution shifts in image classification
R. Taori, A. Dave, V. Shankar, N. Carlini, B. Recht, and L. Schmidt · 2020
Closest in time.
Autocount: Unsupervised segmentation and counting of organs in field images
Jordan R Ubbens, Tewodros W Ayalew, Steve Shirtliffe, Anique Josuttes, Curtis Pozniak, and Ian Stavness · 2020
Closest in time.
Learning when and where to zoom with deep reinforcement learning
B. Uzkent and S. Ermon · 2020
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Scalable learning for bridging the species gap in image-based plant phenotyping
Daniel Ward and Peyman Moghadam · 2020
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Frequency and distribution of chest radiographic findings in covid-19 positive patients
Ho Yuen Frank Wong, Hiu Yin Sonia Lam, Ambrose Ho-Tung Fong, Siu Ting Leung, Thomas Wing-Yan Chin, Christine Shing Yen Lo, Macy Mei-Sze Lui, Jonan Chun Yin Lee, Keith Wan-Hang Chiu, Tom Chung, et al · 2020
Closest in time.
Variational item response theory: Fast, accurate, and expressive
M. Wu, R. L. Davis, B. W. Domingue, C. Piech, and N. Goodman · 2020
Closest in time.
Noise or signal: The role of image backgrounds in object recognition
K. Xiao, L. Engstrom, A. Ilyas, and A. Madry · 2020
Closest in time.
In-N-Out: Pre-training and self-training using auxiliary information for out-of-distribution robustness
S. M. Xie, A. Kumar, R. Jones, F. Khani, T. Ma, and P. Liang · 2020
Closest in time.
Graph-based, self-supervised program repair from diagnostic feedback
Michihiro Yasunaga and Percy Liang · 2020
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Using publicly available satellite imagery and deep learning to understand economic well-being in Africa
C. Yeh, A. Perez, A. Driscoll, G. Azzari, Z. Tang, D. Lobell, S. Ermon, and M. Burke · 2020
Closest in time.
BDD100K: A diverse driving dataset for heterogeneous multitask learning
F. Yu, H. Chen, X. Wang, W. Xian, Y. Chen, F. Liu, V. Madhavan, and T. Darrell · 2020
Closest in time.
Adaptive risk minimization: A meta-learning approach for tackling group shift
M. Zhang, H. Marklund, N. Dhawan, A. Gupta, S. Levine, and C. Finn · 2020
Closest in time.
The curse of performance instability in analysis datasets: Consequences, source, and suggestions
X. Zhou, Y. Nie, H. Tan, and M. Bansal · 2020
Closest in time.
An introduction to electrocatalyst design using machine learning for renewable energy storage
C. L. Zitnick, L. Chanussot, A. Das, S. Goyal, J. Heras-Domingo, C. Ho, W. Hu, T. Lavril, A. Palizhati, M. Riviere, M. Shuaibi, A. Sriram, K. Tran, B. Wood, J. Yoon, D. Parikh, and Z. Ulissi · 2020
Closest in time.
Global wheat head dataset 2021: an update to improve the benchmarking wheat head localization with more diversity, 2021
Etienne David, Mario Serouart, Daniel Smith, Simon Madec, Kaaviya Velumani, Shouyang Liu, Xu Wang, Francisco Pinto Espinosa, Shahameh Shafiee, Izzat S. A. Tahir, Hisashi Tsujimoto, Shuhei Nasuda, Bangyou Zheng, Norbert Kichgessner, Helge Aasen, Andreas Hund, Pouria Sadhegi-Tehran, Koichi Nagasawa, Goro Ishikawa, Sebastien Dandrifosse, Alexis Carlier, Benoit Mercatoris, Ken Kuroki, Haozhou Wang, Masanori Ishii, Minhajul A. Badhon, Curtis Pozniak, David Shaner LeBauer, Morten Lilimo, Jesse Poland, Scott Chapman, Benoit de Solan, Frederic Baret, Ian Stavness, and Wei Guo · 2021
Closest in time.
Learning models with uniform performance via distributionally robust optimization
John Duchi and Hongseok Namkoong · 2021
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The clinician and dataset shift in artificial intelligence
Samuel G. Finlayson, Adarsh Subbaswamy, Karandeep Singh, John Bowers, Annabel Kupke, Jonathan Zittrain, Isaac S. Kohane, and Suchi Saria · 2021
Closest in time.
Selective classification can magnify disparities across groups
Erik Jones, Shiori Sagawa, Pang Wei Koh, Ananya Kumar, and Percy Liang · 2021
Closest in time.
Codexglue: A machine learning benchmark dataset for code understanding and generation
Shuai Lu, Daya Guo, Shuo Ren, Junjie Huang, Alexey Svyatkovskiy, Ambrosio Blanco, Colin Clement, Dawn Drain, Daxin Jiang, Duyu Tang, Ge Li, Lidong Zhou, Linjun Shou, Long Zhou, Michele Tufano, Ming Gong, Ming Zhou, Nan Duan, Neel Sundaresan, Shao Kun Deng, Shengyu Fu, and Shujie Liu · 2021
Closest in time.
Accuracy on the line: on the strong correlation between out-of-distribution and in-distribution generalization
John Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, and Ludwig Schmidt · 2021
Closest in time.
Chromatin accessibility profiling methods
Liesbeth Minnoye, Georgi K Marinov, Thomas Krausgruber, Lixia Pan, Alexandre P Marand, Stefano Secchia, William J Greenleaf, Eileen EM Furlong, Keji Zhao, Robert J Schmitz, et al · 2021
Closest in time.
Spatially resolved mass spectrometry at the single cell: Recent innovations in proteomics and metabolomics
Michael J Taylor, Jessica K Lukowski, and Christopher R Anderton · 2021
Closest in time.