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2020 – today
- 2023
[j11]Bingrong Sun
, Lin Gong, Jisup Shim, Kitae Jang, B. Brian Park, Hongning Wang, Jia Hu:
A human-centric machine learning based personalized route choice prediction in navigation systems. J. Intell. Transp. Syst. 27(4): 523-535 (2023)- [c115]Chuanhao Li, Huazheng Wang, Mengdi Wang, Hongning Wang:
Learning Kernelized Contextual Bandits in a Distributed and Asynchronous Environment. ICLR 2023 - [c114]Lu Lin, Jinghui Chen, Hongning Wang:
Spectral Augmentation for Self-Supervised Learning on Graphs. ICLR 2023 - [c113]Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu:
How Bad is Top-K Recommendation under Competing Content Creators? ICML 2023: 39674-39701 - [c112]Qing Zhang, Xiaoying Zhang, Yang Liu, Hongning Wang, Min Gao, Jiheng Zhang, Ruocheng Guo:
Debiasing Recommendation by Learning Identifiable Latent Confounders. KDD 2023: 3353-3363 - [c111]Huazheng Wang, Haifeng Xu, Chuanhao Li, Zhiyuan Liu, Hongning Wang:
Incentivizing Exploration in Linear Contextual Bandits under Information Gap. RecSys 2023: 415-425 - [c110]Mingzhe Wu, Fan Yao, Hongning Wang:
An End-to-End Solution for Spatial Inference in Smart Buildings. BuildSys@SenSys 2023: 110-119 - [c109]Anat Hashavit, Hongning Wang, Tamar Stern, Sarit Kraus:
Not Just Skipping: Understanding the Effect of Sponsored Content on Users' Decision-Making in Online Health Search. SIGIR 2023: 1056-1065 - [c108]Ye Gao, Brian R. Baucom, Karen Rose, Kristina Gordon, Hongning Wang, John A. Stankovic:
E-ADDA: Unsupervised Adversarial Domain Adaptation Enhanced by a New Mahalanobis Distance Loss for Smart Computing. SMARTCOMP 2023: 172-179 - [c107]Zhendong Chu, Hongning Wang, Yun Xiao, Bo Long, Lingfei Wu:
Meta Policy Learning for Cold-Start Conversational Recommendation. WSDM 2023: 222-230 - [c106]Xiaoying Zhang, Hongning Wang, Hang Li:
Disentangled Representation for Diversified Recommendations. WSDM 2023: 490-498 - [c105]Sudarshan Lamkhede, Anlei Dong, Moumita Bhattacharya, Hongning Wang:
Personalization and Recommendations in Search. WWW (Companion Volume) 2023: 746 - [i60]Xiaoying Zhang, Hongning Wang, Hang Li:
Disentangled Representation for Diversified Recommendations. CoRR abs/2301.05492 (2023) - [i59]Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu:
How Bad is Top-K Recommendation under Competing Content Creators? CoRR abs/2302.01971 (2023) - [i58]Qing Zhang, Xiaoying Zhang, Yang Liu, Hongning Wang, Min Gao, Jiheng Zhang, Ruocheng Guo:
Debiasing Recommendation by Learning Identifiable Latent Confounders. CoRR abs/2302.05052 (2023) - [i57]Zhendong Chu, Hongning Wang:
Meta-Reinforcement Learning via Exploratory Task Clustering. CoRR abs/2302.07958 (2023) - [i56]Xiaoying Zhang, Junpu Chen, Hongning Wang, Hong Xie, Hang Li:
Uncertainty-Aware Off-Policy Learning. CoRR abs/2303.06389 (2023) - [i55]Fan Yao, Chuanhao Li, Karthik Abinav Sankararaman, Yiming Liao, Yan Zhu, Qifan Wang, Hongning Wang, Haifeng Xu:
Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial? CoRR abs/2306.07893 (2023) - [i54]Zhepei Wei, Chuanhao Li, Haifeng Xu, Hongning Wang:
Incentivized Communication for Federated Bandits. CoRR abs/2309.11702 (2023) - [i53]Haozhe Ji, Pei Ke, Hongning Wang, Minlie Huang:
Language Model Decoding as Direct Metrics Optimization. CoRR abs/2310.01041 (2023) - [i52]Zhendong Chu, Nan Wang, Hongning Wang:
Multi-Objective Intrinsic Reward Learning for Conversational Recommender Systems. CoRR abs/2310.20109 (2023) - [i51]Jiale Cheng, Xiao Liu, Kehan Zheng, Pei Ke, Hongning Wang, Yuxiao Dong, Jie Tang, Minlie Huang:
Black-Box Prompt Optimization: Aligning Large Language Models without Model Training. CoRR abs/2311.04155 (2023) - [i50]Pei Ke, Bosi Wen, Zhuoer Feng, Xiao Liu, Xuanyu Lei, Jiale Cheng, Shengyuan Wang, Aohan Zeng, Yuxiao Dong, Hongning Wang, Jie Tang, Minlie Huang:
CritiqueLLM: Scaling LLM-as-Critic for Effective and Explainable Evaluation of Large Language Model Generation. CoRR abs/2311.18702 (2023) - [i49]Xiao Liu, Xuanyu Lei, Shengyuan Wang, Yue Huang, Zhuoer Feng, Bosi Wen, Jiale Cheng, Pei Ke, Yifan Xu, Weng Lam Tam, Xiaohan Zhang, Lichao Sun, Hongning Wang, Jing Zhang, Minlie Huang, Yuxiao Dong, Jie Tang:
AlignBench: Benchmarking Chinese Alignment of Large Language Models. CoRR abs/2311.18743 (2023) - 2022
- [j10]Ye Gao, Asif Salekin, Kristina Gordon, Karen Rose, Hongning Wang, John A. Stankovic:
Emotion Recognition Robust to Indoor Environmental Distortions and Non-targeted Emotions Using Out-of-distribution Detection. ACM Trans. Comput. Heal. 3(2): 15:1-15:22 (2022) - [j9]Hongning Wang:
Big Data Security Management Countermeasures in the Prevention and Control of Computer Network Crime. J. Glob. Inf. Manag. 30(7): 1-16 (2022) - [j8]Ye Gao, Jason Jabbour, Emma C. Schlegel, Meiyi Ma, Matthew McCall, Lahiru N. S. Wijayasingha, Eunjung Ko, Kristina Gordon, Karen Rose, Hongning Wang, John A. Stankovic:
Out-of-the-Box Deployment to Support Research on In-Home Care of Alzheimer's Patients. IEEE Pervasive Comput. 21(1): 37-47 (2022) - [c104]Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu:
Learning the Optimal Recommendation from Explorative Users. AAAI 2022: 9457-9465 - [c103]Chuanhao Li, Hongning Wang:
Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits. AISTATS 2022: 6529-6553 - [c102]A. S. M. Ahsan-Ul-Haque, Hongning Wang:
Rethinking Conversational Recommendations: Is Decision Tree All You Need? CIKM 2022: 686-695 - [c101]Yiling Jia, Weitong Zhang, Dongruo Zhou, Quanquan Gu, Hongning Wang:
Learning Neural Contextual Bandits through Perturbed Rewards. ICLR 2022 - [c100]Huazheng Wang, Haifeng Xu, Hongning Wang:
When Are Linear Stochastic Bandits Attackable? ICML 2022: 23254-23273 - [c99]Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu:
Learning from a Learning User for Optimal Recommendations. ICML 2022: 25382-25406 - [c98]Nan Wang, Hongning Wang, Maryam Karimzadehgan, Branislav Kveton, Craig Boutilier:
IMO^3: Interactive Multi-Objective Off-Policy Optimization. IJCAI 2022: 3523-3529 - [c97]Lu Lin, Ethan Blaser, Hongning Wang:
Graph Structural Attack by Perturbing Spectral Distance. KDD 2022: 989-998 - [c96]Chuanhao Li, Hongning Wang:
Communication Efficient Federated Learning for Generalized Linear Bandits. NeurIPS 2022 - [c95]Chuanhao Li, Huazheng Wang, Mengdi Wang, Hongning Wang:
Communication Efficient Distributed Learning for Kernelized Contextual Bandits. NeurIPS 2022 - [c94]Huazheng Wang, David Zhao, Hongning Wang:
Dynamic Global Sensitivity for Differentially Private Contextual Bandits. RecSys 2022: 179-187 - [c93]Yiling Jia, Hongning Wang:
Scalable Exploration for Neural Online Learning to Rank with Perturbed Feedback. SIGIR 2022: 533-545 - [c92]Lu Lin, Ethan Blaser, Hongning Wang:
Graph Embedding with Hierarchical Attentive Membership. WSDM 2022: 582-590 - [c91]Yiling Jia, Hongning Wang:
Learning Neural Ranking Models Online from Implicit User Feedback. WWW 2022: 431-441 - [c90]Nan Wang, Lu Lin, Jundong Li, Hongning Wang:
Unbiased Graph Embedding with Biased Graph Observations. WWW 2022: 1423-1433 - [c89]Peng Wang, Renqin Cai, Hongning Wang:
Graph-based Extractive Explainer for Recommendations. WWW 2022: 2163-2171 - [c88]Aobo Yang, Nan Wang, Renqin Cai, Hongbo Deng, Hongning Wang:
Comparative Explanations of Recommendations. WWW 2022: 3113-3123 - [i48]Yiling Jia, Hongning Wang:
Learning Neural Ranking Models Online from Implicit User Feedback. CoRR abs/2201.06658 (2022) - [i47]Nan Wang, Hongning Wang, Maryam Karimzadehgan, Branislav Kveton, Craig Boutilier:
IMO3: Interactive Multi-Objective Off-Policy Optimization. CoRR abs/2201.09798 (2022) - [i46]Yiling Jia, Weitong Zhang, Dongruo Zhou, Quanquan Gu, Hongning Wang:
Learning Contextual Bandits Through Perturbed Rewards. CoRR abs/2201.09910 (2022) - [i45]Ye Gao, Brian R. Baucom, Karen Rose, Kristina Gordon, Hongning Wang, John A. Stankovic:
The Enforced Transfer: A Novel Domain Adaptation Algorithm. CoRR abs/2201.10001 (2022) - [i44]Chuanhao Li, Hongning Wang:
Communication Efficient Federated Learning for Generalized Linear Bandits. CoRR abs/2202.01087 (2022) - [i43]Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu:
Learning from a Learning User for Optimal Recommendations. CoRR abs/2202.01879 (2022) - [i42]Peng Wang, Renqin Cai, Hongning Wang:
Graph-based Extractive Explainer for Recommendations. CoRR abs/2202.09730 (2022) - [i41]Zhendong Chu, Hongning Wang, Yun Xiao, Bo Long, Lingfei Wu:
Meta Policy Learning for Cold-Start Conversational Recommendation. CoRR abs/2205.11788 (2022) - [i40]Chuanhao Li, Huazheng Wang, Mengdi Wang, Hongning Wang:
Communication Efficient Distributed Learning for Kernelized Contextual Bandits. CoRR abs/2206.04835 (2022) - [i39]Yiling Jia, Hongning Wang:
Scalable Exploration for Neural Online Learning to Rank with Perturbed Feedback. CoRR abs/2206.05954 (2022) - [i38]Anat Hashavit, Hongning Wang, Tamar Stern, Sarit Kraus:
Not Just Skipping. Understanding the Effect of Sponsored Content on Users' Decision-Making in Online Health Search. CoRR abs/2207.04445 (2022) - [i37]Huazheng Wang, David Zhao, Hongning Wang:
Dynamic Global Sensitivity for Differentially Private Contextual Bandits. CoRR abs/2208.14555 (2022) - [i36]A. S. M. Ahsan-Ul-Haque, Hongning Wang:
Rethinking Conversational Recommendations: Is Decision Tree All You Need? CoRR abs/2208.14614 (2022) - [i35]Lu Lin, Jinghui Chen, Hongning Wang:
Spectral Augmentation for Self-Supervised Learning on Graphs. CoRR abs/2210.00643 (2022) - [i34]Nan Wang, Shaoliang Nie, Qifan Wang, Yi-Chia Wang, Maziar Sanjabi, Jingzhou Liu, Hamed Firooz, Hongning Wang:
COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation. CoRR abs/2210.15500 (2022) - [i33]Ye Gao, Zhendong Chu, Hongning Wang, John A. Stankovic:
MiddleGAN: Generate Domain Agnostic Samples for Unsupervised Domain Adaptation. CoRR abs/2211.03144 (2022) - [i32]Ye Gao, Jason Jabbour, Eunjung Ko, Lahiru Nuwan Wijayasingha, Sooyoung Kim, Zetao Wang, Meiyi Ma, Karen Rose, Kristina Gordon, Hongning Wang, John A. Stankovic:
Integrating Voice-Based Machine Learning Technology into Complex Home Environments. CoRR abs/2211.03149 (2022) - 2021
- [c87]Zhendong Chu, Jing Ma, Hongning Wang:
Learning from Crowds by Modeling Common Confusions. AAAI 2021: 5832-5840 - [c86]Chuanhao Li, Qingyun Wu, Hongning Wang:
Unifying Clustered and Non-stationary Bandits. AISTATS 2021: 1063-1071 - [c85]Zhendong Chu, Hongning Wang:
Improve Learning from Crowds via Generative Augmentation. KDD 2021: 167-175 - [c84]Andrew Villca-Rocha, Max Zheng, Chengzhu Duan, Hongning Wang:
Towards semantic search in building sensor data. BuildSys@SenSys 2021: 164-167 - [c83]Anat Hashavit, Hongning Wang, Raz Lin, Tamar Stern, Sarit Kraus:
Understanding and Mitigating Bias in Online Health Search. SIGIR 2021: 265-274 - [c82]Renqin Cai, Jibang Wu, Aidan San, Chong Wang, Hongning Wang:
Category-aware Collaborative Sequential Recommendation. SIGIR 2021: 388-397 - [c81]Chuanhao Li, Qingyun Wu, Hongning Wang:
When and Whom to Collaborate with in a Changing Environment: A Collaborative Dynamic Bandit Solution. SIGIR 2021: 1410-1419 - [c80]Huazheng Wang, Yiling Jia, Hongning Wang:
Interactive Information Retrieval with Bandit Feedback. SIGIR 2021: 2658-2661 - [c79]Nan Wang, Zhen Qin, Xuanhui Wang, Hongning Wang:
Non-Clicks Mean Irrelevant? Propensity Ratio Scoring As a Correction. WSDM 2021: 481-489 - [c78]Aobo Yang, Nan Wang, Hongbo Deng, Hongning Wang:
Explanation as a Defense of Recommendation. WSDM 2021: 1029-1037 - [c77]Yiling Jia, Huazheng Wang, Stephen Guo, Hongning Wang:
PairRank: Online Pairwise Learning to Rank by Divide-and-Conquer. WWW 2021: 146-157 - [i31]Aobo Yang, Nan Wang, Hongbo Deng, Hongning Wang:
Explanation as a Defense of Recommendation. CoRR abs/2101.09656 (2021) - [i30]Fan Yao, Renqin Cai, Hongning Wang:
Reversible Action Design for Combinatorial Optimization with Reinforcement Learning. CoRR abs/2102.07210 (2021) - [i29]Yiling Jia, Huazheng Wang, Stephen Guo, Hongning Wang:
PairRank: Online Pairwise Learning to Rank by Divide-and-Conquer. CoRR abs/2103.00368 (2021) - [i28]Huazheng Wang, Haifeng Xu, Chuanhao Li, Zhiyuan Liu, Hongning Wang:
Incentivizing Exploration in Linear Bandits under Information Gap. CoRR abs/2104.03860 (2021) - [i27]Chuanhao Li, Qingyun Wu, Hongning Wang:
When and Whom to Collaborate with in a Changing Environment: A Collaborative Dynamic Bandit Solution. CoRR abs/2104.07150 (2021) - [i26]Zhendong Chu, Hongning Wang:
Improve Learning from Crowds via Generative Augmentation. CoRR abs/2107.10449 (2021) - [i25]Chuanhao Li, Hongning Wang:
Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits. CoRR abs/2110.01463 (2021) - [i24]Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu:
Learning the Optimal Recommendation from Explorative Users. CoRR abs/2110.03068 (2021) - [i23]Huazheng Wang, Haifeng Xu, Hongning Wang:
When Are Linear Stochastic Bandits Attackable? CoRR abs/2110.09008 (2021) - [i22]Nan Wang, Lu Lin, Jundong Li, Hongning Wang:
Unbiased Graph Embedding with Biased Graph Observations. CoRR abs/2110.13957 (2021) - [i21]Lu Lin, Ethan Blaser, Hongning Wang:
Graph Embedding with Hierarchical Attentive Membership. CoRR abs/2111.00604 (2021) - [i20]Aobo Yang, Nan Wang, Renqin Cai, Hongbo Deng, Hongning Wang:
Comparative Explanations of Recommendations. CoRR abs/2111.00670 (2021) - [i19]Lu Lin, Ethan Blaser, Hongning Wang:
Graph Structural Attack by Spectral Distance. CoRR abs/2111.00684 (2021) - [i18]Yiling Jia, Hongning Wang:
Calibrating Explore-Exploit Trade-off for Fair Online Learning to Rank. CoRR abs/2111.00735 (2021) - 2020
- [c76]Shuheng Li, Dezhi Hong, Hongning Wang:
Relation Inference among Sensor Time Series in Smart Buildings with Metric Learning. AAAI 2020: 4683-4690 - [c75]Rithwik Kukunuri, Nipun Batra, Hongning Wang:
Lessons and Insights from Super-Resolution of Energy Data. COMAD/CODS 2020: 355-356 - [c74]Jing Ma, Dezhi Hong, Hongning Wang:
Selective Sampling for Sensor Type Classification in Buildings. IPSN 2020: 241-252 - [c73]Nan Wang, Hongning Wang:
Directional Multivariate Ranking. KDD 2020: 85-94 - [c72]Lu Lin, Hongning Wang:
Graph Attention Networks over Edge Content-Based Channels. KDD 2020: 1819-1827 - [c71]Qingyun Wu, Huazheng Wang, Hongning Wang:
Learning by Exploration: New Challenges in Real-World Environments. KDD 2020: 3575-3576 - [c70]Huazheng Wang, Qian Zhao, Qingyun Wu, Shubham Chopra, Abhinav Khaitan, Hongning Wang:
Global and Local Differential Privacy for Collaborative Bandits. RecSys 2020: 150-159 - [c69]Rithwik Kukunuri, Nipun Batra, Hongning Wang:
An Open Problem: Energy Data Super-Resolution. NILM@SenSys 2020: 99-102 - [c68]Ye Gao, Meiyi Ma, Kristina Gordon, Karen Rose, Hongning Wang, John A. Stankovic:
A monitoring, modeling, and interactive recommendation system for in-home caregivers: demo abstract. SenSys 2020: 587-588 - [c67]Lin Gong, Lu Lin, Weihao Song, Hongning Wang:
JNET: Learning User Representations via Joint Network Embedding and Topic Embedding. WSDM 2020: 205-213 - [c66]Jibang Wu, Renqin Cai, Hongning Wang:
Déjà vu: A Contextualized Temporal Attention Mechanism for Sequential Recommendation. WWW 2020: 2199-2209 - [i17]Jibang Wu, Renqin Cai, Hongning Wang:
Déjà vu: A Contextualized Temporal Attention Mechanism for Sequential Recommendation. CoRR abs/2002.00741 (2020) - [i16]Nan Wang, Xuanhui Wang, Hongning Wang:
Unbiased Learning to Rank via Propensity Ratio Scoring. CoRR abs/2005.08480 (2020) - [i15]Nan Wang, Hongning Wang:
Directional Multivariate Ranking. CoRR abs/2006.09978 (2020) - [i14]Chuanhao Li, Qingyun Wu, Hongning Wang:
Unifying Clustered and Non-stationary Bandits. CoRR abs/2009.02463 (2020) - [i13]Zhendong Chu, Jing Ma, Hongning Wang:
Learning from Crowds by Modeling Common Confusions. CoRR abs/2012.13052 (2020)
2010 – 2019
- 2019
- [c65]Zhendong Chu, Renqin Cai, Hongning Wang:
Accounting for Temporal Dynamics in Document Streams. CIKM 2019: 1813-1822 - [c64]Yiling Jia, Nipun Batra, Hongning Wang, Kamin Whitehouse:
Active Collaborative Sensing for Energy Breakdown. CIKM 2019: 1943-1952 - [c63]Huazheng Wang, Zhe Gan, Xiaodong Liu, Jingjing Liu, Jianfeng Gao, Hongning Wang:
Adversarial Domain Adaptation for Machine Reading Comprehension. EMNLP/IJCNLP (1) 2019: 2510-2520 - [c62]Qingyun Wu, Zhige Li, Huazheng Wang, Wei Chen, Hongning Wang:
Factorization Bandits for Online Influence Maximization. KDD 2019: 636-646 - [c61]Xueying Bai, Jian Guan, Hongning Wang:
A Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation. NeurIPS 2019: 10734-10745 - [c60]Lu Lin, Zheng Luo, Dezhi Hong, Hongning Wang:
Sequential Learning with Active Partial Labeling for Building Metadata. BuildSys@SenSys 2019: 189-192 - [c59]Dezhi Hong, Renqin Cai, Hongning Wang, Kamin Whitehouse:
Learning from Correlated Events for Equipment Relation Inference in Buildings. BuildSys@SenSys 2019: 203-212 - [c58]Yiyi Tao, Yiling Jia, Nan Wang, Hongning Wang:
The FacT: Taming Latent Factor Models for Explainability with Factorization Trees. SIGIR 2019: 295-304 - [c57]Wasi Uddin Ahmad, Kai-Wei Chang, Hongning Wang:
Context Attentive Document Ranking and Query Suggestion. SIGIR 2019: 385-394 - [c56]Huazheng Wang, Sonwoo Kim, Eric McCord-Snook, Qingyun Wu, Hongning Wang:
Variance Reduction in Gradient Exploration for Online Learning to Rank. SIGIR 2019: 835-844 - [c55]Lu Lin, Lin Gong, Hongning Wang:
Learning Personalized Topical Compositions with Item Response Theory. WSDM 2019: 609-617 - [c54]Qingyun Wu, Huazheng Wang, Yanen Li, Hongning Wang:
Dynamic Ensemble of Contextual Bandits to Satisfy Users' Changing Interests. WWW 2019: 2080-2090 - [c53]Yiling Jia, Nipun Batra, Hongning Wang, Kamin Whitehouse:
A Tree-Structured Neural Network Model for Household Energy Breakdown. WWW 2019: 2872-2878 - [i12]Yiyi Tao, Yiling Jia, Nan Wang, Hongning Wang:
The FacT: Taming Latent Factor Models for Explainability with Factorization Trees. CoRR abs/1906.02037 (2019) - [i11]Wasi Uddin Ahmad, Kai-Wei Chang, Hongning Wang:
Context Attentive Document Ranking and Query Suggestion. CoRR abs/1906.02329 (2019) - [i10]Qingyun Wu, Zhige Li, Huazheng Wang, Wei Chen,