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Graph Structural Attack by Spectral Distance


Nov 03, 2021
Lu Lin, Ethan Blaser, Hongning Wang


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Calibrating Explore-Exploit Trade-off for Fair Online Learning to Rank


Nov 01, 2021
Yiling Jia, Hongning Wang


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Graph Structural Attack by Spectral Distanc


Nov 01, 2021
Lu Lin, Ethan Blaser, Hongning Wang


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Comparative Explanations of Recommendations


Nov 01, 2021
Aobo Yang, Nan Wang, Renqin Cai, Hongbo Deng, Hongning Wang

* 17 pages, 4 figures 

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Graph Embedding with Hierarchical Attentive Membership


Oct 31, 2021
Lu Lin, Ethan Blaser, Hongning Wang

* to be published in WSDM 2022 

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Unbiased Graph Embedding with Biased Graph Observations


Oct 29, 2021
Nan Wang, Lu Lin, Jundong Li, Hongning Wang


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When Are Linear Stochastic Bandits Attackable?


Oct 18, 2021
Huazheng Wang, Haifeng Xu, Hongning Wang


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Learning the Optimal Recommendation from Explorative Users


Oct 06, 2021
Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu


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Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits


Oct 04, 2021
Chuanhao Li, Hongning Wang

* 27 pages, 4 figures 

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Improve Learning from Crowds via Generative Augmentation


Jul 22, 2021
Zhendong Chu, Hongning Wang

* KDD 2021 

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When and Whom to Collaborate with in a Changing Environment: A Collaborative Dynamic Bandit Solution


Apr 14, 2021
Chuanhao Li, Qingyun Wu, Hongning Wang


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Incentivizing Exploration in Linear Bandits under Information Gap


Apr 08, 2021
Huazheng Wang, Haifeng Xu, Chuanhao Li, Zhiyuan Liu, Hongning Wang


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PairRank: Online Pairwise Learning to Rank by Divide-and-Conquer


Mar 03, 2021
Yiling Jia, Huazheng Wang, Stephen Guo, Hongning Wang

* The co-authors do not agree to open access this paper. We ask for a withdrawal now 

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Reversible Action Design for Combinatorial Optimization with Reinforcement Learning


Feb 14, 2021
Fan Yao, Renqin Cai, Hongning Wang


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Explanation as a Defense of Recommendation


Jan 24, 2021
Aobo Yang, Nan Wang, Hongbo Deng, Hongning Wang

* WSDM 2021 

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Learning from Crowds by Modeling Common Confusions


Dec 24, 2020
Zhendong Chu, Jing Ma, Hongning Wang

* Accepted by AAAI 2021 

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Unifying Clustered and Non-stationary Bandits


Sep 05, 2020
Chuanhao Li, Qingyun Wu, Hongning Wang

* 26 pages, 3 figures 

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Directional Multivariate Ranking


Jun 09, 2020
Nan Wang, Hongning Wang

* Accepted as a full research paper in KDD'20 

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Unbiased Learning to Rank via Propensity Ratio Scoring


May 18, 2020
Nan Wang, Xuanhui Wang, Hongning Wang


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Déjà vu: A Contextualized Temporal Attention Mechanism for Sequential Recommendation


Jan 29, 2020
Jibang Wu, Renqin Cai, Hongning Wang

* Key Words: Sequential Recommendation, Self-attention mechanism, Temporal Recommendation 

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Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation


Nov 13, 2019
Xueying Bai, Jian Guan, Hongning Wang


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A Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation


Nov 10, 2019
Xueying Bai, Jian Guan, Hongning Wang


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BPMR: Bayesian Probabilistic Multivariate Ranking


Sep 18, 2019
Nan Wang, Hongning Wang


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Active Collaborative Sensing for Energy Breakdown


Sep 02, 2019
Yiling Jia, Nipun Batra, Hongning Wang, Kamin Whitehouse

* 12 pages, CIKM 2019 

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Adversarial Domain Adaptation for Machine Reading Comprehension


Aug 24, 2019
Huazheng Wang, Zhe Gan, Xiaodong Liu, Jingjing Liu, Jianfeng Gao, Hongning Wang

* Accepted to EMNLP 2019 

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Factorization Bandits for Online Influence Maximization


Jul 16, 2019
Qingyun Wu, Zhige Li, Huazheng Wang, Wei Chen, Hongning Wang

* 11 pages (including SUPPLEMENT) 

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The FacT: Taming Latent Factor Models for Explainability with Factorization Trees


Jun 03, 2019
Yiyi Tao, Yiling Jia, Nan Wang, Hongning Wang

* In proceedings of SIGIR'19 

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Explainable Recommendation via Multi-Task Learning in Opinionated Text Data


Jun 10, 2018
Nan Wang, Hongning Wang, Yiling Jia, Yue Yin

* 10 pages, SIGIR 2018 

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Learning Contextual Bandits in a Non-stationary Environment


May 23, 2018
Qingyun Wu, Naveen Iyer, Hongning Wang

* 10 pages, 13 figures, To appear on ACM Special Interest Group on Information Retrieval (SIGIR) 2018 

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