Robust Ranking Explanations

8 July 2023

Papers citing "Robust Ranking Explanations"

50 / 62 papers shown

Title
Robust Explanation Constraints for Neural Networks Matthew Wicker Juyeon Heo Luca Costabello Adrian Weller FAtt 42 18 0 16 Dec 2022
Exploiting the Relationship Between Kendall's Rank Correlation and Cosine Similarity for Attribution Protection Fan Wang A. Kong 139 10 0 15 May 2022
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 260 348 0 15 Dec 2021
Self-learn to Explain Siamese Networks Robustly Chao Chen Yifan Shen Guixiang Ma Xiangnan Kong S. Rangarajan Xi Zhang Sihong Xie 65 5 0 15 Sep 2021
Robust Explainability: A Tutorial on Gradient-Based Attribution Methods for Deep Neural Networks Ian E. Nielsen Dimah Dera Ghulam Rasool N. Bouaynaya R. Ramachandran FAtt 69 80 0 23 Jul 2021
Certifiably Robust Interpretation via Renyi Differential Privacy Ao Liu Xiaoyu Chen Sijia Liu Lirong Xia Chuang Gan AAML 47 13 0 04 Jul 2021
Improving Attribution Methods by Learning Submodular Functions Piyushi Manupriya Tarun Ram Menta S. Jagarlapudi V. Balasubramanian TDI 53 6 0 19 Apr 2021
Practical Relative Order Attack in Deep Ranking Mo Zhou Le Wang Zhenxing Niu Qilin Zhang Yinghui Xu N. Zheng G. Hua 106 18 0 09 Mar 2021
QAIR: Practical Query-efficient Black-Box Attacks for Image Retrieval Xiaodan Li Jinfeng Li YueFeng Chen Shaokai Ye Yuan He Shuhui Wang Hang Su Hui Xue 55 44 0 04 Mar 2021
Towards Robust and Reliable Algorithmic Recourse Sohini Upadhyay Shalmali Joshi Himabindu Lakkaraju 52 109 0 26 Feb 2021
Enhanced Regularizers for Attributional Robustness A. Sarkar Anirban Sarkar V. Balasubramanian 41 16 0 28 Dec 2020
Towards Robust Explanations for Deep Neural Networks Ann-Kathrin Dombrowski Christopher J. Anders K. Müller Pan Kessel FAtt 62 63 0 18 Dec 2020
Augmented Lagrangian Adversarial Attacks Jérôme Rony Eric Granger M. Pedersoli Ismail Ben Ayed AAML 42 39 0 24 Nov 2020
Towards Understanding the Regularization of Adversarial Robustness on Neural Networks Yuxin Wen Shuai Li Kui Jia AAML 47 24 0 15 Nov 2020
FAR: A General Framework for Attributional Robustness Adam Ivankay Ivan Girardi Chiara Marchiori P. Frossard OOD 50 22 0 14 Oct 2020
Input Hessian Regularization of Neural Networks Waleed Mustafa Robert A. Vandermeulen Marius Kloft AAML 46 12 0 14 Sep 2020
A simple defense against adversarial attacks on heatmap explanations Laura Rieger Lars Kai Hansen FAtt AAML 71 37 0 13 Jul 2020
Boundary thickness and robustness in learning models Yaoqing Yang Rekha Khanna Yaodong Yu A. Gholami Kurt Keutzer Joseph E. Gonzalez Kannan Ramchandran Michael W. Mahoney OOD 41 41 0 09 Jul 2020
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data Zhun Deng Linjun Zhang Amirata Ghorbani James Zou 67 32 0 15 Jun 2020
Towards Understanding Fast Adversarial Training Bai Li Shiqi Wang Suman Jana Lawrence Carin AAML 63 50 0 04 Jun 2020
Transferable, Controllable, and Inconspicuous Adversarial Attacks on Person Re-identification With Deep Mis-Ranking Hongjun Wang Guangrun Wang Ya Li Dongyu Zhang Liang Lin AAML 52 84 0 08 Apr 2020
Toward Adversarial Robustness via Semi-supervised Robust Training Yiming Li Baoyuan Wu Yan Feng Yanbo Fan Yong Jiang Zhifeng Li Shutao Xia AAML 101 13 0 16 Mar 2020
Adversarial Ranking Attack and Defense Mo Zhou Zhenxing Niu Le Wang Qilin Zhang G. Hua 110 39 0 26 Feb 2020
Understanding and Mitigating the Tradeoff Between Robustness and Accuracy Aditi Raghunathan Sang Michael Xie Fanny Yang John C. Duchi Percy Liang AAML 84 228 0 25 Feb 2020
DANCE: Enhancing saliency maps using decoys Y. Lu Wenbo Guo Masashi Sugiyama William Stafford Noble AAML 52 14 0 03 Feb 2020
GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks Q. Huang M. Yamada Yuan Tian Dinesh Singh Dawei Yin Yi-Ju Chang FAtt 82 354 0 17 Jan 2020
Fast is better than free: Revisiting adversarial training Eric Wong Leslie Rice J. Zico Kolter AAML OOD 138 1,178 0 12 Jan 2020
ERASER: A Benchmark to Evaluate Rationalized NLP Models Jay DeYoung Sarthak Jain Nazneen Rajani Eric P. Lehman Caiming Xiong R. Socher Byron C. Wallace 112 637 0 08 Nov 2019
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review Han Xu Yao Ma Haochen Liu Debayan Deb Hui Liu Jiliang Tang Anil K. Jain AAML 65 675 0 17 Sep 2019
Targeted Mismatch Adversarial Attack: Query with a Flower to Retrieve the Tower Giorgos Tolias Filip Radenovic Ondřej Chum AAML 52 70 0 24 Aug 2019
Explanations can be manipulated and geometry is to blame Ann-Kathrin Dombrowski Maximilian Alber Christopher J. Anders M. Ackermann K. Müller Pan Kessel AAML FAtt 81 331 0 19 Jun 2019
Is Attention Interpretable? Sofia Serrano Noah A. Smith 108 683 0 09 Jun 2019
On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems Tianyi Lin Chi Jin Michael I. Jordan 120 507 0 02 Jun 2019
Explainability Techniques for Graph Convolutional Networks Federico Baldassarre Hossein Azizpour GNN FAtt 168 268 0 31 May 2019
Robust Attribution Regularization Jiefeng Chen Xi Wu Vaibhav Rastogi Yingyu Liang S. Jha OOD 47 83 0 23 May 2019
Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations R. Mothilal Amit Sharma Chenhao Tan CML 108 1,020 0 19 May 2019
Explaining Deep Neural Networks with a Polynomial Time Algorithm for Shapley Values Approximation Marco Ancona Cengiz Öztireli Markus Gross FAtt TDI 81 225 0 26 Mar 2019
Neural Network Attributions: A Causal Perspective Aditya Chattopadhyay Piyushi Manupriya Anirban Sarkar V. Balasubramanian CML 50 146 0 06 Feb 2019
Fooling Neural Network Interpretations via Adversarial Model Manipulation Juyeon Heo Sunghwan Joo Taesup Moon AAML FAtt 93 203 0 06 Feb 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 134 2,549 0 24 Jan 2019
Robustness via curvature regularization, and vice versa Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi J. Uesato P. Frossard AAML 74 319 0 23 Nov 2018
Theoretical Analysis of Adversarial Learning: A Minimax Approach Zhuozhuo Tu Jingwei Zhang Dacheng Tao AAML 43 68 0 13 Nov 2018
Sanity Checks for Saliency Maps Julius Adebayo Justin Gilmer M. Muelly Ian Goodfellow Moritz Hardt Been Kim FAtt AAML XAI 134 1,966 0 08 Oct 2018
On the Robustness of Interpretability Methods David Alvarez-Melis Tommi Jaakkola 76 526 0 21 Jun 2018
Towards Robust Interpretability with Self-Explaining Neural Networks David Alvarez-Melis Tommi Jaakkola MILM XAI 126 941 0 20 Jun 2018
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 102 1,778 0 30 May 2018
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives Amit Dhurandhar Pin-Yu Chen Ronny Luss Chun-Chen Tu Pai-Shun Ting Karthikeyan Shanmugam Payel Das FAtt 115 589 0 21 Feb 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 219 3,185 0 01 Feb 2018
Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution Judea Pearl CML 61 335 0 11 Jan 2018
Interpretation of Neural Networks is Fragile Amirata Ghorbani Abubakar Abid James Zou FAtt AAML 131 866 0 29 Oct 2017