Robust Explainable Recommendation

3 May 2024

Papers citing "Robust Explainable Recommendation"

26 / 26 papers shown

Title
Knowledge-aware Coupled Graph Neural Network for Social Recommendation Chao Huang Huance Xu Yong-mei Xu Peng Dai Lianghao Xia Mengyin Lu Liefeng Bo Hao Xing Xiaoping Lai Yanfang Ye 54 172 0 08 Oct 2021
Counterfactual Explainable Recommendation Juntao Tan Shuyuan Xu Yingqiang Ge Yunqi Li Xu Chen Yongfeng Zhang CML 51 145 0 24 Aug 2021
Jointly Attacking Graph Neural Network and its Explanations Wenqi Fan Wei Jin Xiaorui Liu Han Xu Xianfeng Tang Suhang Wang Qing Li Jiliang Tang Jianping Wang Charu C. Aggarwal AAML 54 28 0 07 Aug 2021
Personalized Transformer for Explainable Recommendation Lei Li Yongfeng Zhang Li Chen 102 139 0 25 May 2021
Building Reliable Explanations of Unreliable Neural Networks: Locally Smoothing Perspective of Model Interpretation Dohun Lim Hyeonseok Lee Sungchan Kim FAtt AAML 51 13 0 26 Mar 2021
Robust and Stable Black Box Explanations Himabindu Lakkaraju Nino Arsov Osbert Bastani AAML FAtt 53 84 0 12 Nov 2020
Multi-Step Adversarial Perturbations on Recommender Systems Embeddings Vito Walter Anelli Alejandro Bellogín Yashar Deldjoo Tommaso Di Noia Felice Antonio Merra AAML 18 5 0 03 Oct 2020
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective G. R. Machado Eugênio Silva R. Goldschmidt AAML 60 161 0 08 Sep 2020
Fairness-Aware Explainable Recommendation over Knowledge Graphs Zuohui Fu Yikun Xian Ruoyuan Gao Jieyu Zhao Qiaoying Huang ... Shuyuan Xu Shijie Geng C. Shah Yongfeng Zhang Gerard de Melo FaML 94 206 0 03 Jun 2020
White Noise Analysis of Neural Networks Ali Borji Sikun Lin FAtt 30 12 0 23 Dec 2019
Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods Dylan Slack Sophie Hilgard Emily Jia Sameer Singh Himabindu Lakkaraju FAtt AAML MLAU 68 817 0 06 Nov 2019
Hierarchical Attentive Knowledge Graph Embedding for Personalized Recommendation Xiao Sha Zhu Sun Jie Zhang 77 63 0 18 Oct 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
On the Connection Between Adversarial Robustness and Saliency Map Interpretability Christian Etmann Sebastian Lunz Peter Maass Carola-Bibiane Schönlieb AAML FAtt 58 161 0 10 May 2019
Fooling Neural Network Interpretations via Adversarial Model Manipulation Juyeon Heo Sunghwan Joo Taesup Moon AAML FAtt 93 202 0 06 Feb 2019
Sanity Checks for Saliency Maps Julius Adebayo Justin Gilmer M. Muelly Ian Goodfellow Moritz Hardt Been Kim FAtt AAML XAI 123 1,965 0 08 Oct 2018
Adversarial Personalized Ranking for Recommendation Xiangnan He Zhankui He Xiaoyu Du Tat-Seng Chua 80 396 0 12 Aug 2018
On the Robustness of Interpretability Methods David Alvarez-Melis Tommi Jaakkola 76 526 0 21 Jun 2018
Explainable Recommendation via Multi-Task Learning in Opinionated Text Data Nan Wang Hongning Wang Yiling Jia Yue Yin 40 205 0 10 Jun 2018
Explainable Recommendation: A Survey and New Perspectives Yongfeng Zhang Xu Chen XAI LRM 79 876 0 30 Apr 2018
Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients A. Ross Finale Doshi-Velez AAML 147 681 0 26 Nov 2017
The (Un)reliability of saliency methods Pieter-Jan Kindermans Sara Hooker Julius Adebayo Maximilian Alber Kristof T. Schütt Sven Dähne D. Erhan Been Kim FAtt XAI 91 685 0 02 Nov 2017
Towards Interpretable Deep Neural Networks by Leveraging Adversarial Examples Yinpeng Dong Hang Su Jun Zhu Fan Bao AAML 119 129 0 18 Aug 2017
Automatic Generation of Natural Language Explanations F. Costa Sixun Ouyang Peter Dolog A. Lawlor 90 97 0 04 Jul 2017
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.7K 150,006 0 22 Dec 2014
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 264 19,045 0 20 Dec 2014