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Although neural networks (especially deep neural networks) have achieved \textit{better-than-human} performance in many fields, their real-world deployment is still questionable due to the lack of awareness about the limitation in their knowledge.
Improving MAE against CCE under Label Noise
Xinshao Wang, Elyor Kodirov, Yang Hua, and Neil Martin Robertson. 2019c · 1903
Earlier work this paper cites.
SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver
Po-Wei Wang, Priya L. Donti, Bryan Wilder, and J. Zico Kolter. 2019a · 1905
Earlier work this paper cites.
Emphasis Regularisation by Gradient Rescaling for Training Deep Neural Networks with Noisy Labels
Xinshao Wang, Yang Hua, Elyor Kodirov, and Neil Martin Robertson. 2019b · 1905
Earlier work this paper cites.
Online Active Learning of Reject Option Classifiers
Kulin Shah and Naresh Manwani. 2019 · 1906
Earlier work this paper cites.
A symbol classifier able to reject wrong shapes for document recognition systems. In 3rd International Workshop on Graphics Recognition, GREC 1999, September 26, 1999 - September 27, 1999 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 1941) . Springer Verlag, -, 209–218
Eric Anquetil, Bertrand Couasnon, and Frederic Dambreville. 1999 · 1941
Earlier work this paper cites.
An optimum character recognition system using decision functions
C. K. Chow. 1957 · 1957
Earlier work this paper cites.
Evaluation of a training method and of various rejection criteria for a neural network classifier used for off-line signature verification. In Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7), June 27, 1994 - June 29, 1994 (IEEE International Conference on Neural Networks - Conference Proceedings, Vol. 7) . IEEE, -, 4294–4299
Jean-Pierre Drouhard, Robert Sabourin, and Mario Godbout. 1994 · 1994
Earlier work this paper cites.
Classification rejection by prediction. In 1996 International Conference on Artificial Neural Networks, ICANN 1996, July 16, 1996 - July 19, 1996 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 1112 LNCS) . Springer Verlag, -, 293–298
H. De Lassus, Ph Daigremont, F. Badran, S. Thiria, and A. Lecacheux. 1996 · 1996
Earlier work this paper cites.
An RBF based classifier for the detection of microcalcifications in mammograms with outlier rejection capability. In 1997 IEEE International Conference on Neural Networks, ICNN 1997, June 9, 1997 - June 12, 1997 (IEEE International Conference on Neural Networks - Conference Proceedings, Vol. 3) . Institute of Electrical and Electronics Engineers Inc., -, 1379–1384
A. Hojjatoleslami, L. Sardo, and J. Kittler. 1997 · 1997
Earlier work this paper cites.
Interior-point methods
Florian A. Potra and Stephen J. Wright. 2000 · 2000
Earlier work this paper cites.
Injection of human knowledge into the rejection criterion of a neural network classifier. In Joint 9th IFSA World Congress and 20th NAFIPS International Conference, July 25, 2001 - July 28, 2001 (Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS, Vol. 1) . Institute of Electrical and Electronics Engineers Inc., -, 499–505
Xuejing Wu and C. Y. Suen. 2001 · 2001
Earlier work this paper cites.
Fine-grained Uncertainty Modeling in Neural Networks
Rahul Soni, Naresh Shah, and Jimmy D. Moore. 2020 · 2002
Earlier work this paper cites.
An effective reject rule for reliability improvement in bank note neuro-classifiers. In 13th IEEE Workshop on Neural Networks for Signal Processing, NNSP 2003, September 17, 2003 - September 19, 2003 (Neural Networks for Signal Processing - Proceedings of the IEEE Workshop, Vol. 2003-January) . Institute of Electrical and Electronics Engineers Inc., -, 509–516
Ali Ahmadi, Sigeru Omatu, and Toshihisa Kosaka. 2003 · 2003
Earlier work this paper cites.
Bayesian applications of belief networks and multilayer perceptrons for ovarian tumor classification with rejection
Peter Antal, Geert Fannes, Dirk Timmerman, Yves Moreau, and Bart De Moor. 2003 · 2003
Earlier work this paper cites.
A holistic classification system for check amounts based on neural networks with rejection. In 1st International Conference on Pattern Recognition and Machine Intelligence, PReMI 2005, December 20, 2005 - December 22, 2005 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 3776 LNCS) . Springer Verlag, -, 310–314
M. J. Castro, W. Diaz, F. J. Ferri, J. Ruiz-Pinales, R. Jaime-Rivas, F. Blat, S. Espana, P. Aibar, S. Grau, and D. Griol. 2005 · 2005
Earlier work this paper cites.
Classification of remote sensing data by multistage self-organizing maps with rejection schemes. In RAST 2005 - 2nd International Conference on Recent Advances in Space Technologies, June 9, 2005 - June 11, 2005 (RAST 2005 - Proceedings of 2nd International Conference on Recent Advances in Space Technologies, Vol. 2005) . Inst. of Elec. and Elec. Eng. Computer Society, -, 534–539
Jaejoon Lee and Okan K. Ersoy. 2005 · 2005
Earlier work this paper cites.
ProSelfLC: Progressive Self Label Correction for Target Revising in Label Noise
Xinshao Wang, Yang Hua, Elyor Kodirov, and Neil Martin Robertson. 2020 · 2005
Earlier work this paper cites.
Regression with reject option and application to kNN
Christophe Denis, Mohamed Hebiri, and Ahmed Zaoui. 2020 · 2006
Earlier work this paper cites.
Support Vector Machines with a Reject Option. In Advances in Neural Information Processing Systems , D. Koller, D. Schuurmans, Y. Bengio, and L. Bottou (Eds.), Vol. 21. Curran Associates, Inc., -
Yves Grandvalet, Alain Rakotomamonjy, Joseph Keshet, and Stéphane Canu. 2008 · 2008
Earlier work this paper cites.
Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
Earlier work this paper cites.
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement
David Moher, Alessandro Liberati, Jennifer Tetzlaff, Douglas G. Altman, and The PRISMA Group. 2009 · 2009
Earlier work this paper cites.
Understanding Spatial Robustness of Deep Neural Networks
Ziyuan Zhong, Yuchi Tian, and Baishakhi Ray. 2020 · 2010
Earlier work this paper cites.
Building gene expression profile classifiers with a simple and efficient rejection option in R. In 10th International Conference on Bioinformatics and 1st ISCB Asia Joint Conference 2011: Bioinformatics, InCoB 2011/ISCB-Asia 2011, November 30, 2011 - December 2, 2011 , Vol. 12. BioMed Central Ltd, Asia, 10th International Conference on Bioinformatics – 1st ISCB Asia Joint Conference 2011, InCoB 2011/ISCB–Asia 2011: Bioinformatics – Proceedings from Asia Pacific Bioinformatics Network (APBioNet)
Alfredo Benso, Stefano Di Carlo, Gianfranco Politano, Alessandro Savino, and Hafeez Hafeezurrehman. 2011 · 2011
Earlier work this paper cites.
Rejection measurement based on linear discriminant analysis for document recognition
Chun Lei He, Louisa Lam, and Ching Y. Suen. 2011 · 2011
Earlier work this paper cites.
Reading Digits in Natural Images with Unsupervised Feature Learning. In NIPS Workshop on Deep Learning and Unsupervised Feature Learning 2011 . -, -, –
Yuval Netzer, Tao Wang, Adam Coates, Alessandro Bissacco, Bo Wu, and Andrew Y. Ng. 2011 · 2011
Earlier work this paper cites.
Possibilistic network-based classifiers: On the reject option and concept drift issues. In 5th International Conference on Scalable Uncertainty Management, SUM 2011, October 10, 2011 - October 13, 2011 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 6929 LNAI) . Springer Verlag, -, 460–474
Karim Tabia. 2011 · 2011
Earlier work this paper cites.
Multi-modal Fusion based on classifiers using reject options and Markov Fusion Networks. In 21st International Conference on Pattern Recognition, ICPR 2012, November 11, 2012 - November 15, 2012 (Proceedings - International Conference on Pattern Recognition) . Institute of Electrical and Electronics Engineers Inc., -, 1084–1087
Michael Glodek, Martin Schels, Gunther Palm, and Friedhelm Schwenker. 2012a · 2012
Earlier work this paper cites.
Multiple classifier combination using reject options and markov fusion networks. In 14th ACM International Conference on Multimodal Interaction, ICMI 2012, October 22, 2012 - October 26, 2012 (ICMI’12 - Proceedings of the ACM International Conference on Multimodal Interaction) . Association for Computing Machinery, -, 465–472
Michael Glodek, Martin Schels, Gunther Palm, and Friedhelm Schwenker. 2012b · 2012
Earlier work this paper cites.
Interpretability and Explainability: A Machine Learning Zoo Mini-tour
Ricards Marcinkevics and Julia E. Vogt. 2020 · 2012
Earlier work this paper cites.
Highly accurate recognition of human postures and activities through classification with rejection
Wenlong Tang and Edward S. Sazonov. 2014 · 2013
Earlier work this paper cites.
A novel pattern rejection criterion based on multiple classifiers. In 11th International Workshop on Multiple Classifier Systems, MCS 2013, May 15, 2013 - May 17, 2013 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 7872 LNCS) . Springer Verlag, -, 331–342
Wei-Na Wang, Xu-Yao Zhang, and Ching Y. Suen. 2013 · 2013
Earlier work this paper cites.
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan and Andrew Zisserman. 2014 · 2014
Earlier work this paper cites.
Classification with reject option using the self-organizing map. In 24th International Conference on Artificial Neural Networks, ICANN 2014, September 15, 2014 - September 19, 2014 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 8681 LNCS) . Springer Verlag, -, 105–112
Ricardo Sousa, Ajalmar R. Da Rocha Neto, Jaime S. Cardoso, and Guilherme A. Barreto. 2014 · 2014
Earlier work this paper cites.
Siamese neural network based similarity metric for inertial gesture classification and rejection. In 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015, May 4, 2015 - May 8, 2015 (2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015) . Institute of Electrical and Electronics Engineers Inc., -, Baidu; et al.; IEEE Biometrics Council; IEEE Computer Society; NSF; VideoLectures
Samuel Berlemont, Gregoire Lefebvre, Stefan Duffner, and Christophe Garcia. 2015 · 2015
Earlier work this paper cites.
Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2015 · 2015
Earlier work this paper cites.
Towards Open Set Deep Networks. In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) . IEEE Computer Society, Los Alamitos, CA, USA, 1563–1572
A. Bendale and T. E. Boult. 2016 · 2016
Earlier work this paper cites.
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning. In Proceedings of The 33rd International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 48) , Maria Florina Balcan and Kilian Q. Weinberger (Eds.). PMLR, New York, New York, USA, 1050–1059
Yarin Gal and Zoubin Ghahramani. 2016 · 2016
Earlier work this paper cites.
Deep Learning
Ian Goodfellow, Yoshua Bengio, and Aaron Courville. 2016 · 2016
Earlier work this paper cites.
Logic Tensor Networks: Deep Learning and Logical Reasoning from Data and Knowledge
Luciano Serafini and Artur S. d’Avila Garcez. 2016 · 2016
Cited alongside, same era.
Exploit All the Layers: Fast and Accurate CNN Object Detector with Scale Dependent Pooling and Cascaded Rejection Classifiers. In 29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016, June 26, 2016 - July 1, 2016 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 2016-December) . IEEE Computer Society, -, 2129–2137
Fan Yang, Wongun Choi, and Yuanqing Lin. 2016 · 2016
Cited alongside, same era.
Improving the Robustness of Deep Neural Networks via Stability Training
Stephan Zheng, Yang Song, Thomas Leung, and Ian J. Goodfellow. 2016 · 2016
Cited alongside, same era.
A Closer Look at Memorization in Deep Networks. In Proceedings of the 34th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 70) , Doina Precup and Yee Whye Teh (Eds.). PMLR, -, 233–242
An Effective Baseline for Robustness to Distributional Shift
Sunil Thulasidasan, Sushil Thapa, Sayera Dhaubhadel, Gopinath Chennupati, Tanmoy Bhattacharya, and Jeff A. Bilmes. 2021 · 2021
Later among the works it cites.
Mixup Gamblers: Learning to Abstain with Auto-Calibrated Reward for Mixed Samples. In Artificial Neural Networks and Machine Learning – ICANN 2021 , Igor Farkaš, Paolo Masulli, Sebastian Otte, and Stefan Wermter (Eds.). Springer International Publishing, Cham, 287–294
Takumi Yamaguchi and Masahiro Murakawa. 2021 · 2021
Later among the works it cites.
Generalized Out-of-Distribution Detection: A Survey
Jingkang Yang, Kaiyang Zhou, Yixuan Li, and Ziwei Liu. 2021 · 2021
Later among the works it cites.
Understanding deep learning (still) requires rethinking generalization
Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, and Oriol Vinyals. 2021a · 2021
Later among the works it cites.
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Devansh Arpit, Stanisław Jastrzębski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron Courville, Yoshua Bengio, and Simon Lacoste-Julien. 2017 · 2017
Cited alongside, same era.
Explanation and justification in machine learning: A survey. In IJCAI-17 workshop on explainable AI (XAI) , Vol. 8. -, -, 8–13
Or Biran and Courtenay Cotton. 2017 · 2017
Cited alongside, same era.
A novel approach for mobile robot localization in topological maps using classification with reject option from structural co-occurrence matrix. In 17th International Conference on Computer Analysis of Images and Patterns, CAIP 2017, August 22, 2017 - August 24, 2017 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 10424 LNCS) . Springer Verlag, -, 3–15
Suane Pires P. da Silva, Leandro B. Marinho, Jefferson S. Almeida, and Pedro Pedrosa Reboucas Filho. 2018 · 2017
Cited alongside, same era.
Selective classification for deep neural networks. In 31st Annual Conference on Neural Information Processing Systems, NIPS 2017, December 4, 2017 - December 9, 2017 (Advances in Neural Information Processing Systems, Vol. 2017-December) . Neural information processing systems foundation, Long Beach California, 4879–4888
Yonatan Geifman and Ran El-Yaniv. 2017 · 2017
Cited alongside, same era.
Explainable artificial intelligence (xai)
David Gunning. 2017 · 2017
Cited alongside, same era.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
Amina Adadi and Mohammed Berrada. 2018 · 2018
Cited alongside, same era.
Localization of Mobile Robots with Topological Maps and Classification with Reject Option using Convolutional Neural Networks in Omnidirectional Images. In 2018 International Joint Conference on Neural Networks, IJCNN 2018, July 8, 2018 - July 13, 2018 (Proceedings of the International Joint Conference on Neural Networks, Vol. 2018-July) . Institute of Electrical and Electronics Engineers Inc., -, –
Suane Pires P. Da Silva, Raul Victor M. Da Nobrega, Aldisio G. Medeiros, Leandro B. Marinho, Jefferson S. Almeida, and Pedro Pedrosa Reboucas Filho. 2018 · 2018
Cited alongside, same era.
Trainable Calibration Measures for Neural Networks from Kernel Mean Embeddings. In Proceedings of the 35th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 80) , Jennifer Dy and Andreas Krause (Eds.). PMLR, -, 2805–2814
Aviral Kumar, Sunita Sarawagi, and Ujjwal Jain. 2018 · 2018
Cited alongside, same era.
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Jared Leon-Malpartida, Jeanfranco D. Farfan-Escobedo, and Gladys E. Cutipa-Arapa. 2018 · 2018
Cited alongside, same era.
A Neural Rejection System Against Universal Adversarial Perturbations in Radio Signal Classification. In 2021 IEEE Global Communications Conference, GLOBECOM 2021, December 7, 2021 - December 11, 2021 (2021 IEEE Global Communications Conference, GLOBECOM 2021 - Proceedings) . Institute of Electrical and Electronics Engineers Inc., -, et al.; Huawei; Intel; Qualcomm; Vodafone; ZTE
Lu Zhang, Sangarapillai Lambotharan, Gan Zheng, and Fabio Roli. 2021b · 2021
Later among the works it cites.
The need for quantification of uncertainty in artificial intelligence for clinical data analysis: increasing the level of trust in the decision-making process
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Later among the works it cites.
Generalized Learning with Rejection for Classification and Regression Problems. (2019)
Amina Asif and Fayyaz ul Amir Afsar Minhas. 2019 · 2022
Later among the works it cites.
Fault diagnosis by Bayesian network classifiers with a distance rejection criterion. In 16th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2019, July 29, 2019 - July 31, 2019 (ICINCO 2019 - Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics, Vol. 1) . SciTePress, -, 463–468
M. Amine Atoui, Achraf Cohen, Phillipe Rauffet, and Pascal Berruet. 2019 · 2022
Later among the works it cites.
CNN Confidence Estimation for Rejection-Based Hand Gesture Classification in Myoelectric Control
Tianzhe Bao, Syed Ali Raza Zaidi, Sheng Quan Xie, Pengfei Yang, and Zhi-Qiang Zhang. 2022 · 2022
Later among the works it cites.
Controlled abstention neural networks for identifying skillful predictions for classification problems. (2021)
Elizabeth A. Barnes and Randal J. Barnes. 2021a · 2022
Later among the works it cites.
Controlled abstention neural networks for identifying skillful predictions for regression problems. (2021)
Elizabeth A. Barnes and Randal J. Barnes. 2021b · 2022
Later among the works it cites.
Optimally ordering IDK classifiers subject to deadlines
Sanjoy Baruah, Alan Burns, Robert I. Davis, and Yue Wu. 2022 · 2022
Later among the works it cites.
Selective Classification of Sequential Data Using Inductive Conformal Prediction. In 2022 IEEE International Conference on Assured Autonomy, ICAA 2022, March 22, 2022 - March 24, 2022 (Proceeding - 2022 IEEE International Conference on Assured Autonomy, ICAA 2022) . Institute of Electrical and Electronics Engineers Inc., -, 46–55
Dimitrios Boursinos and Xenofon Koutsoukos. 2022 · 2022
Later among the works it cites.
Trading via selective classification. (2021)
Nestoras Chalkidis and Rahul Savani. 2021 · 2022
Later among the works it cites.
To reject or not to reject: that is the question - an answer in case of neural classifiers
Claudio De Stefano, Carlo Sansone, and Mario Vento. 2000 · 2022
Later among the works it cites.
Selective prediction-set models with coverage rate guarantees. (2019)
Jean Feng, Arjun Sondhi, Jessica Perry, and Noah Simon. 2019 · 2022
Later among the works it cites.
Calibrated Selective Classification
Adam Fisch, Tommi Jaakkola, and Regina Barzilay. 2022 · 2022
Later among the works it cites.
Reject option with multiple thresholds
Giorgio Fumera, Fabio Roli, and Giorgio Giacinto. 2000 · 2022
Later among the works it cites.
Deep learning with logical constraints
Eleonora Giunchiglia, Mihaela Catalina Stoian, and Thomas Lukasiewicz. 2022 · 2022
Later among the works it cites.
RISAN: Robust instance specific abstention network. (2021)
Bhavya Kalra, Kulin Shah, and Naresh Manwani. 2021 · 2022
Later among the works it cites.
IDPS Signature Classification with a Reject Option and the Incorporation of Expert Knowledge
Hidetoshi Kawaguchi, Yuichi Nakatani, and Shogo Okada. 2022 · 2022
Later among the works it cites.
Dependency decomposition and a reject option for explainable models. (2020)
Jan H. Kronenberger and Anselm Haselhoff. 2020 · 2022
Later among the works it cites.
Hyperspectral open set classification with unknown classes rejection towards deep networks
Yu Liu, Yuhua Tang, Lixiong Zhang, Lu Liu, Minghui Song, Kecheng Gong, Yuanxi Peng, Jing Hou, and Tian Jiang. 2020 · 2022
Later among the works it cites.
Fine-grained TLS Services Classification with Reject Option. (2022)
Jan Luxemburk and Toma ejka. 2022 · 2022
Later among the works it cites.
Classification of Traffic Using Neural Networks by Rejecting: a Novel Approach in Classifying VPN Traffic. (2020)
Ali Parchekani, Salar Nouri, Vahid Shah-Mansouri, and Seyed Pooya Shariatpanahi. 2020 · 2022
Later among the works it cites.
A UNIFIED DENSITY-DRIVEN FRAMEWORK FOR EFFECTIVE DATA DENOISING AND ROBUST ABSTENTION. In 2021 IEEE International Conference on Image Processing, ICIP 2021, September 19, 2021 - September 22, 2021 (Proceedings - International Conference on Image Processing, ICIP, Vol. 2021-September) . IEEE Computer Society, -, 594–598
Krishanu Sarker, Xiulong Yang, Yang Li, Saeid Belkasim, and Shihao Ji. 2021 · 2022
Later among the works it cites.
Classification System with Capability to Reject Unknowns. In 2019 IEEE International Conference on Imaging Systems and Techniques, IST 2019, December 8, 2019 - December 10, 2019 (IST 2019 - IEEE International Conference on Imaging Systems and Techniques, Proceedings) . Institute of Electrical and Electronics Engineers Inc., Abu Dhabi, 1558–2809
Soma Shiraishi, Katsumi Kikuchi, and Kota Iwamoto. 2019 · 2022
Later among the works it cites.
Combating label noise in deep learning using abstention. (2019)
Sunil Thulasidasan, Tanmoy Bhattacharya, Jeffrey Bilmes, Gopinath Chennupati, and Jamaludin Mohd-Yusof. 2019 · 2022
Later among the works it cites.
Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes. (2021)
Yu Tian, Yuyuan Liu, Guansong Pang, Fengbei Liu, Yuanhong Chen, and Gustavo Carneiro. 2021 · 2022
Later among the works it cites.
Reliable Visual Question Answering: Abstain Rather Than Answer Incorrectly
Spencer Whitehead, Suzanne Petryk, Vedaad Shakib, Joseph Gonzalez, Trevor Darrell, Anna Rohrbach, and Marcus Rohrbach. 2022 · 2022
Later among the works it cites.
Augmenting Softmax Information for Selective Classification with Out-of-Distribution Data
Guoxuan Xia and Christos-Savvas Bouganis. 2022 · 2022
Later among the works it cites.
Learning Algorithm in Two-Stage Selective Prediction. In 2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML) . -, -, 512–521
Weicheng Ye, Dangxing Chen, and Ilqar Ramazanli. 2022 · 2022
Later among the works it cites.
Leveraging uncertainty in deep learning for selective classification. (2019)
Mehmet Yigit Yildirim, Mert Ozer, and Hasan Davulcu. 2019 · 2022
Later among the works it cites.
Improve Robustness and Accuracy of Deep Neural Network with L 2 , ∞ L_{2,\infty} Normalization
Lijia Yu and Xiao-Shan Gao. 2022 · 2022
Later among the works it cites.
Deep-RBF networks revisited: Robust classification with rejection. (2018)
Pourya Habib Zadeh, Reshad Hosseini, and Suvrit Sra. 2018 · 2022
Later among the works it cites.
A Deep Bayesian Neural Network for Cardiac Arrhythmia Classification with Rejection from ECG Recordings. (2022)
Wenrui Zhang, Xinxin Di, Guodong Wei, Shijia Geng, Zhaoji Fu, and Shenda Hong. 2022 · 2022
Later among the works it cites.
Deep gamblers: Learning to abstain with portfolio theory. (2019)
Liu Ziyin, Zhikang T. Wang, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency, and Masahito Ueda. 2019 · 2022
Later among the works it cites.