Selective Classification for Deep Neural Networks

23 May 2017

Papers citing "Selective Classification for Deep Neural Networks"

50 / 321 papers shown

Title
Ground-truth or DAER: Selective Re-query of Secondary Information Stephan J. Lemmer Jason J. Corso 14 4 0 16 Sep 2020
Into the Unknown: Active Monitoring of Neural Networks Anna Lukina Christian Schilling T. Henzinger AAML 32 27 0 14 Sep 2020
Solving Long-tailed Recognition with Deep Realistic Taxonomic Classifier Tz-Ying Wu Pedro Morgado Pei Wang Chih-Hui Ho Nuno Vasconcelos 13 45 0 20 Jul 2020
Efficient Conformal Prediction via Cascaded Inference with Expanded Admission Adam Fisch Tal Schuster Tommi Jaakkola Regina Barzilay 16 1 0 06 Jul 2020
Confidence-Aware Learning for Deep Neural Networks J. Moon Jihyo Kim Younghak Shin Sangheum Hwang UQCV 28 144 0 03 Jul 2020
Classification Confidence Estimation with Test-Time Data-Augmentation Yuval Bahat Gregory Shakhnarovich 8 17 0 30 Jun 2020
Selective Question Answering under Domain Shift Amita Kamath Robin Jia Percy Liang OOD 21 206 0 16 Jun 2020
Calibrating Deep Neural Network Classifiers on Out-of-Distribution Datasets Zhihui Shao Jianyi Yang Shaolei Ren OODD 35 11 0 16 Jun 2020
Weakly-supervised Temporal Action Localization by Uncertainty Modeling Pilhyeon Lee Jinglu Wang Yan Lu H. Byun EDL 25 11 0 12 Jun 2020
PLANS: Robust Program Learning from Neurally Inferred Specifications Raphaël Dang-Nhu 30 2 0 05 Jun 2020
Consistent Estimators for Learning to Defer to an Expert Hussein Mozannar David Sontag 15 198 0 02 Jun 2020
SIPA: A Simple Framework for Efficient Networks Gihun Lee Sangmin Bae Jaehoon Oh Seyoung Yun 16 1 0 24 Apr 2020
SoQal: Selective Oracle Questioning in Active Learning Dani Kiyasseh T. Zhu David Clifton 35 0 0 22 Apr 2020
SCOUT: Self-aware Discriminant Counterfactual Explanations Pei Wang Nuno Vasconcelos FAtt 30 81 0 16 Apr 2020
Budget Learning via Bracketing Aditya Gangrade D. A. E. Acar Venkatesh Saligrama 59 8 0 14 Apr 2020
Towards Automating the AI Operations Lifecycle Matthew Arnold Jeffrey Boston Michael Desmond Evelyn Duesterwald Benjamin Elder Anupama Murthi Jirí Navrátil Darrell Reimer 10 9 0 28 Mar 2020
Synthesize then Compare: Detecting Failures and Anomalies for Semantic Segmentation Yingda Xia Yi Zhang Fengze Liu Wei Shen Alan Yuille UQCV 27 149 0 18 Mar 2020
Utilizing Network Properties to Detect Erroneous Inputs Matt Gorbett Nathaniel Blanchard AAML 23 6 0 28 Feb 2020
Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution Data Yen-Chang Hsu Yilin Shen Hongxia Jin Z. Kira OODD 24 561 0 26 Feb 2020
Self-Adaptive Training: beyond Empirical Risk Minimization Lang Huang Chaoning Zhang Hongyang R. Zhang NoLa 29 198 0 24 Feb 2020
Adversarial Robustness for Code Pavol Bielik Martin Vechev AAML 22 89 0 11 Feb 2020
On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation N. Brosse C. Riquelme Alice Martin Sylvain Gelly Eric Moulines BDL OOD UQCV 19 33 0 22 Jan 2020
Dirichlet uncertainty wrappers for actionable algorithm accuracy accountability and auditability José Mena O. Pujol Jordi Vitrià 21 8 0 29 Dec 2019
Practical Solutions for Machine Learning Safety in Autonomous Vehicles Sina Mohseni Mandar Pitale Vasu Singh Zhangyang Wang 33 67 0 20 Dec 2019
On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration Kanil Patel William H. Beluch Dan Zhang Michael Pfeiffer Bin Yang UQCV 29 30 0 16 Dec 2019
Outside the Box: Abstraction-Based Monitoring of Neural Networks T. Henzinger Anna Lukina Christian Schilling AAML 38 59 0 20 Nov 2019
Doppler Spectrum Classification with CNNs via Heatmap Location Encoding and a Multi-head Output Layer A. Gilbert M. Holden L. Eikvil Mariia Rakhmail Aleksandar Babić S. Aase E. Samset K. Mcleod 28 2 0 06 Nov 2019
Generative Well-intentioned Networks J. Cosentino Jun Zhu AI4CE 22 2 0 28 Oct 2019
Detecting Out-of-Distribution Inputs in Deep Neural Networks Using an Early-Layer Output Vahdat Abdelzad Krzysztof Czarnecki Rick Salay Taylor Denouden Sachin Vernekar Buu Phan OODD 27 46 0 23 Oct 2019
Deep Neural Rejection against Adversarial Examples Angelo Sotgiu Ambra Demontis Marco Melis Battista Biggio Giorgio Fumera Xiaoyi Feng Fabio Roli AAML 22 68 0 01 Oct 2019
Addressing Failure Prediction by Learning Model Confidence Charles Corbière Nicolas Thome Avner Bar-Hen Matthieu Cord P. Pérez 33 283 0 01 Oct 2019
Deep Gamblers: Learning to Abstain with Portfolio Theory Liu Ziyin Zhikang T. Wang Paul Pu Liang Ruslan Salakhutdinov Louis-Philippe Morency Masahito Ueda 26 111 0 29 Jun 2019
Selective prediction-set models with coverage guarantees Jean Feng A. Sondhi Jessica Perry N. Simon 19 7 0 13 Jun 2019
Efficient Evaluation-Time Uncertainty Estimation by Improved Distillation Erik Englesson Hossein Azizpour UQCV 19 8 0 12 Jun 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 77 1,662 0 06 Jun 2019
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks S. Thulasidasan Gopinath Chennupati J. Bilmes Tanmoy Bhattacharya S. Michalak UQCV 34 529 0 27 May 2019
Combating Label Noise in Deep Learning Using Abstention S. Thulasidasan Tanmoy Bhattacharya J. Bilmes Gopinath Chennupati J. Mohd-Yusof NoLa 22 178 0 27 May 2019
Controlling Risk of Web Question Answering Lixin Su Jiafeng Guo Yixing Fan Yanyan Lan Xueqi Cheng 21 9 0 24 May 2019
Leveraging Uncertainty in Deep Learning for Selective Classification M. Yildirim M. Ozer H. Davulcu 21 10 0 23 May 2019
Better the Devil you Know: An Analysis of Evasion Attacks using Out-of-Distribution Adversarial Examples Vikash Sehwag A. Bhagoji Liwei Song Chawin Sitawarin Daniel Cullina M. Chiang Prateek Mittal OODD 32 26 0 05 May 2019
POBA-GA: Perturbation Optimized Black-Box Adversarial Attacks via Genetic Algorithm Jinyin Chen Mengmeng Su Shijing Shen Hui Xiong Haibin Zheng AAML 22 67 0 01 May 2019
Direct Object Recognition Without Line-of-Sight Using Optical Coherence Xin Lei Liangyu He Yixuan Tan K. X. Wang Xinggang Wang Yihan Du S. Fan Zongfu Yu 8 27 0 18 Mar 2019
Towards Structured Evaluation of Deep Neural Network Supervisors Jens Henriksson C. Berger Markus Borg Lars Tornberg Cristofer Englund S. Sathyamoorthy Stig Ursing AAML 9 37 0 04 Mar 2019
Hybrid Models with Deep and Invertible Features Eric T. Nalisnick Akihiro Matsukawa Yee Whye Teh Dilan Görür Balaji Lakshminarayanan BDL DRL 22 99 0 07 Feb 2019
SelectiveNet: A Deep Neural Network with an Integrated Reject Option Yonatan Geifman Ran El-Yaniv CVBM OOD 24 305 0 26 Jan 2019
Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at Label Shift Adaptation Amr M. Alexandari A. Kundaje Avanti Shrikumar 21 9 0 21 Jan 2019
NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature Franz J. Király Bilal A. Mateen R. Sonabend 23 10 0 18 Dec 2018
Recent Advances in Open Set Recognition: A Survey Chuanxing Geng Sheng-Jun Huang Songcan Chen BDL ObjD 59 759 0 21 Nov 2018
Deep Active Learning with a Neural Architecture Search Yonatan Geifman Ran El-Yaniv AI4CE 14 44 0 19 Nov 2018
Focusing on the Big Picture: Insights into a Systems Approach to Deep Learning for Satellite Imagery Ritwik Gupta Carson D. Sestili J. Vazquez-Trejo Matthew E. Gaston VLM 25 2 0 12 Nov 2018