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Books and Theses
- 2014
[b1]Hongning Wang:
Computational user intent modeling. University of Illinois Urbana-Champaign, USA, 2014
Journal Articles
- 2024
- [j12]Meriel von Stein
, Hongning Wang, Sebastian G. Elbaum:
Automated Generation of Transformations to Mitigate Sensor Hardware Migration in ADS. IEEE Robotics Autom. Lett. 9(7): 6480-6487 (2024) - 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) - 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) - 2017
- [j7]Sarah Masud Preum, Md. Abu Sayeed Mondol, Meiyi Ma, Hongning Wang, John A. Stankovic:
Preclude2 : Personalized conflict detection in heterogeneous health applications. Pervasive Mob. Comput. 42: 226-247 (2017) - [j6]Hongning Wang, Rui Li, Milad Shokouhi, Hang Li, Yi Chang:
Search, Mining, and Their Applications on Mobile Devices: Introduction to the Special Issue. ACM Trans. Inf. Syst. 35(4): 29:1-29:17 (2017) - 2016
- [j5]Shengwen Peng, Ronghui You, Hongning Wang, Chengxiang Zhai, Hiroshi Mamitsuka, Shanfeng Zhu:
DeepMeSH: deep semantic representation for improving large-scale MeSH indexing. Bioinform. 32(12): 70-79 (2016) - 2015
- [j4]Peilin Yang, Hongning Wang, Hui Fang, Deng Cai:
Opinions matter: a general approach to user profile modeling for contextual suggestion. Inf. Retr. J. 18(6): 586-610 (2015) - 2014
- [j3]Hongbo Deng, Jiawei Han, Hao Li, Heng Ji, Hongning Wang, Yue Lu:
Exploring and inferring user-user pseudo-friendship for sentiment analysis with heterogeneous networks. Stat. Anal. Data Min. 7(4): 308-321 (2014) - 2009
- [j2]Hongning Wang, Minlie Huang, Xiaoyan Zhu:
Extract interaction detection methods from the biological literature. BMC Bioinform. 10(S-1) (2009) - 2008
- [j1]Hongning Wang, Minlie Huang, Shilin Ding, Xiaoyan Zhu:
Exploiting and integrating rich features for biological literature classification. BMC Bioinform. 9(S-3) (2008)
Conference and Workshop Papers
- 2024
- [c141]Zhendong Chu, Renqin Cai, Hongning Wang:
Meta-Reinforcement Learning via Exploratory Task Clustering. AAAI 2024: 11633-11641 - [c140]Zhiwei Wang, Huazheng Wang, Hongning Wang:
Stealthy Adversarial Attacks on Stochastic Multi-Armed Bandits. AAAI 2024: 15770-15777 - [c139]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. ACL (1) 2024: 3201-3219 - [c138]Zhexin Zhang, Junxiao Yang, Pei Ke, Fei Mi, Hongning Wang, Minlie Huang:
Defending Large Language Models Against Jailbreaking Attacks Through Goal Prioritization. ACL (1) 2024: 8865-8887 - [c137]Xiao Liu, Xuanyu Lei, Shengyuan Wang, Yue Huang, Andrew Feng, Bosi Wen, Jiale Cheng, Pei Ke, Yifan Xu, Weng Lam Tam, Xiaohan Zhang, Lichao Sun, Xiaotao Gu, Hongning Wang, Jing Zhang, Minlie Huang, Yuxiao Dong, Jie Tang:
AlignBench: Benchmarking Chinese Alignment of Large Language Models. ACL (1) 2024: 11621-11640 - [c136]Jiaxin Wen, Ruiqi Zhong, Pei Ke, Zhihong Shao, Hongning Wang, Minlie Huang:
Learning Task Decomposition to Assist Humans in Competitive Programming. ACL (1) 2024: 11700-11723 - [c135]Pei Ke, Bosi Wen, Andrew Feng, Xiao Liu, Xuanyu Lei, Jiale Cheng, Shengyuan Wang, Aohan Zeng, Yuxiao Dong, Hongning Wang, Jie Tang, Minlie Huang:
CritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model Generation. ACL (1) 2024: 13034-13054 - [c134]Ethan Blaser, Chuanhao Li, Hongning Wang:
Federated Linear Contextual Bandits with Heterogeneous Clients. AISTATS 2024: 631-639 - [c133]Jinfeng Zhou, Zhuang Chen, Dazhen Wan, Bosi Wen, Yi Song, Jifan Yu, Yongkang Huang, Pei Ke, Guanqun Bi, Libiao Peng, Jiaming Yang, Xiyao Xiao, Sahand Sabour, Xiaohan Zhang, Wenjing Hou, Yijia Zhang, Yuxiao Dong, Hongning Wang, Jie Tang, Minlie Huang:
CharacterGLM: Customizing Social Characters with Large Language Models. EMNLP (Industry Track) 2024: 1457-1476 - [c132]Jiale Cheng, Yida Lu, Xiaotao Gu, Pei Ke, Xiao Liu, Yuxiao Dong, Hongning Wang, Jie Tang, Minlie Huang:
AutoDetect: Towards a Unified Framework for Automated Weakness Detection in Large Language Models. EMNLP (Findings) 2024: 6786-6803 - [c131]Zhexin Zhang, Yida Lu, Jingyuan Ma, Di Zhang, Rui Li, Pei Ke, Hao Sun, Lei Sha, Zhifang Sui, Hongning Wang, Minlie Huang:
ShieldLM: Empowering LLMs as Aligned, Customizable and Explainable Safety Detectors. EMNLP (Findings) 2024: 10420-10438 - [c130]Haozhe Ji, Pei Ke, Hongning Wang, Minlie Huang:
Language Model Decoding as Direct Metrics Optimization. ICLR 2024 - [c129]Zhepei Wei, Chuanhao Li, Tianze Ren, Haifeng Xu, Hongning Wang:
Incentivized Truthful Communication for Federated Bandits. ICLR 2024 - [c128]Haozhe Ji, Cheng Lu, Yilin Niu, Pei Ke, Hongning Wang, Jun Zhu, Jie Tang, Minlie Huang:
Towards Efficient Exact Optimization of Language Model Alignment. ICML 2024 - [c127]Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu:
Human vs. Generative AI in Content Creation Competition: Symbiosis or Conflict? ICML 2024 - [c126]Fan Yao, Yiming Liao, Mingzhe Wu, Chuanhao Li, Yan Zhu, James Yang, Jingzhou Liu, Qifan Wang, Haifeng Xu, Hongning Wang:
User Welfare Optimization in Recommender Systems with Competing Content Creators. KDD 2024: 3874-3885 - [c125]Michael Bendersky, Cheng Li, Qiaozhu Mei, Vanessa Murdock, Jie Tang, Hongning Wang, Hamed Zamani, Mingyang Zhang, Xingjian Zhang:
The Second Workshop on Large Language Models for Individuals, Groups, and Society. SIGIR 2024: 3062-3064 - [c124]Sudarshan Lamkhede, Hamed Zamani, Moumita Bhattacharya, Hongning Wang:
Third Workshop on Personalization and Recommendations in Search (PaRiS). SIGIR 2024: 3065-3069 - [c123]Michael Bendersky, Cheng Li, Qiaozhu Mei, Vanessa Murdock, Jie Tang, Hongning Wang, Hamed Zamani, Mingyang Zhang:
WSDM 2024 Workshop on Large Language Models for Individuals, Groups, and Society. WSDM 2024: 1206-1207 - [c122]Xiaoying Zhang, Hongning Wang, Yang Liu:
Retention Depolarization in Recommender System. WWW 2024: 1126-1137 - [c121]Kai Zheng, Haijun Zhao, Rui Huang, Beichuan Zhang, Na Mou, Yanan Niu, Yang Song, Hongning Wang, Kun Gai:
Full Stage Learning to Rank: A Unified Framework for Multi-Stage Systems. WWW 2024: 3621-3631 - 2023
- [c120]Nan Wang, Qifan Wang, Yi-Chia Wang, Maziar Sanjabi, Jingzhou Liu, Hamed Firooz, Hongning Wang, Shaoliang Nie:
COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation. EMNLP 2023: 13258-13275 - [c119]Chuanhao Li, Huazheng Wang, Mengdi Wang, Hongning Wang:
Learning Kernelized Contextual Bandits in a Distributed and Asynchronous Environment. ICLR 2023 - [c118]Lu Lin, Jinghui Chen, Hongning Wang:
Spectral Augmentation for Self-Supervised Learning on Graphs. ICLR 2023 - [c117]Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu:
How Bad is Top-K Recommendation under Competing Content Creators? ICML 2023: 39674-39701 - [c116]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 - [c115]Zhendong Chu, Nan Wang, Hongning Wang:
Multi-Objective Intrinsic Reward Learning for Conversational Recommender Systems. NeurIPS 2023 - [c114]Zhepei Wei, Chuanhao Li, Haifeng Xu, Hongning Wang:
Incentivized Communication for Federated Bandits. NeurIPS 2023 - [c113]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? NeurIPS 2023 - [c112]Xiaoying Zhang, Junpu Chen, Hongning Wang, Hong Xie, Yang Liu, John C. S. Lui, Hang Li:
Uncertainty-Aware Instance Reweighting for Off-Policy Learning. NeurIPS 2023 - [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 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 - 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 - 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 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 D. Guo, Hongning Wang:
PairRank: Online Pairwise Learning to Rank by Divide-and-Conquer. WWW 2021: 146-157 - 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 - 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 2019: 189-192 - [c59]Dezhi Hong, Renqin Cai, Hongning Wang, Kamin Whitehouse:
Learning from Correlated Events for Equipment Relation Inference in Buildings. BuildSys 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 - 2018
- [c52]Nipun Batra, Yiling Jia, Hongning Wang, Kamin Whitehouse:
Transferring Decomposed Tensors for Scalable Energy Breakdown Across Regions. AAAI 2018: 740-747 - [c51]Renqin Cai, Xueying Bai, Zhenrui Wang, Yuling Shi, Parikshit Sondhi, Hongning Wang:
Modeling Sequential Online Interactive Behaviors with Temporal Point Process. CIKM 2018: 873-882 - [c50]Wasi Uddin Ahmad, Kai-Wei Chang, Hongning Wang:
Multi-Task Learning for Document Ranking and Query Suggestion. ICLR (Poster) 2018 - [c49]Elaheh Sadredini, Deyuan Guo, Chunkun Bo, Reza Rahimi, Kevin Skadron, Hongning Wang:
A Scalable Solution for Rule-Based Part-of-Speech Tagging on Novel Hardware Accelerators. KDD 2018: 665-674 - [c48]Lin Gong, Hongning Wang:
When Sentiment Analysis Meets Social Network: A Holistic User Behavior Modeling in Opinionated Data. KDD 2018: 1455-1464 - [c47]Yi Qi, Qingyun Wu, Hongning Wang, Jie Tang, Maosong Sun:
Bandit Learning with Implicit Feedback. NeurIPS 2018: 7287-7297 - [c46]Jason Koh, Dezhi Hong, Rajesh K. Gupta, Kamin Whitehouse, Hongning Wang, Yuvraj Agarwal:
Plaster: an integration, benchmark, and development framework for metadata normalization methods. BuildSys 2018: 1-10 - [c45]Huazheng Wang, Ramsey Langley, Sonwoo Kim, Eric McCord-Snook, Hongning Wang:
Efficient Exploration of Gradient Space for Online Learning to Rank. SIGIR 2018: 145-154 - [c44]Nan Wang, Hongning Wang, Yiling Jia, Yue Yin:
Explainable Recommendation via Multi-Task Learning in Opinionated Text Data. SIGIR 2018: 165-174 - [c43]Wasi Uddin Ahmad, Kai-Wei Chang, Hongning Wang:
Intent-aware Query Obfuscation for Privacy Protection in Personalized Web Search. SIGIR 2018: 285-294 - [c42]Qingyun Wu, Naveen Iyer, Hongning Wang:
Learning Contextual Bandits in a Non-stationary Environment. SIGIR 2018: 495-504 - [c41]Puxuan Yu, Wasi Uddin Ahmad, Hongning Wang:
Hide-n-Seek: An Intent-aware Privacy Protection Plugin for Personalized Web Search. SIGIR 2018: 1333-1336 - 2017
- [c40]Huazheng Wang, Qingyun Wu, Hongning Wang:
Factorization Bandits for Interactive Recommendation. AAAI 2017: 2695-2702 - [c39]Nipun Batra, Hongning Wang, Amarjeet Singh, Kamin Whitehouse:
Matrix Factorisation for Scalable Energy Breakdown. AAAI 2017: 4467-4473 - [c38]Asif Salekin, Hongning Wang, Kristine Williams, John A. Stankovic:
DAVE: Detecting Agitated Vocal Events. CHASE 2017: 157-166 - [c37]Yuling Shi, Zhiyong Peng, Hongning Wang:
Modeling Student Learning Styles in MOOCs. CIKM 2017: 979-988 - [c36]Qingyun Wu, Hongning Wang, Liangjie Hong, Yue Shi:
Returning is Believing: Optimizing Long-term User Engagement in Recommender Systems. CIKM 2017: 1927-1936 - [c35]Yue Wang, Hongning Wang, Hui Fang:
Extracting User-Reported Mobile Application Defects from Online Reviews. ICDM Workshops 2017: 422-429 - [c34]Sarah Masud Preum, Md. Abu Sayeed Mondol, Meiyi Ma, Hongning Wang, John A. Stankovic:
Conflict detection in online textual health advice: demo abstract. IPSN 2017: 267-268 - [c33]Sarah Masud Preum, Md. Abu Sayeed Mondol, Meiyi Ma, Hongning Wang, John A. Stankovic:
Preclude: Conflict detection in textual health advice. PerCom 2017: 286-296 - [c32]Renqin Cai, Chi Wang, Hongning Wang:
Accounting for the Correspondence in Commented Data. SIGIR 2017: 365-374 - [c31]Derek Wu, Hongning Wang:
ReviewMiner: An Aspect-based Review Analytics System. SIGIR 2017: 1285-1288 - [c30]Lin Gong, Benjamin Haines, Hongning Wang:
Clustered Model Adaption for Personalized Sentiment Analysis. WWW 2017: 937-946 - 2016
- [c29]Lin Gong, Mohammad Al Boni, Hongning Wang:
Modeling Social Norms Evolution for Personalized Sentiment Classification. ACL (1) 2016 - [c28]Huazheng Wang, Qingyun Wu, Hongning Wang:
Learning Hidden Features for Contextual Bandits. CIKM 2016: 1633-1642 - [c27]Qingyun Wu, Huazheng Wang, Quanquan Gu, Hongning Wang:
Contextual Bandits in a Collaborative Environment. SIGIR 2016: 529-538 - [c26]Wasi Uddin Ahmad, Md. Masudur Rahman, Hongning Wang:
Topic Model based Privacy Protection in Personalized Web Search. SIGIR 2016: 1025-1028 - [c25]Md. Mustafizur Rahman, Hongning Wang:
Hidden Topic Sentiment Model. WWW 2016: 155-165 - 2015
- [c24]Mohammad Al Boni, Keira Zhou, Hongning Wang, Matthew S. Gerber:
Model Adaptation for Personalized Opinion Analysis. ACL (2) 2015: 769-774 - [c23]Dezhi Hong, Hongning Wang, Kamin Whitehouse:
Clustering-based Active Learning on Sensor Type Classification in Buildings. CIKM 2015: 363-372 - [c22]Dezhi Hong, Hongning Wang, Jorge Ortiz, Kamin Whitehouse:
The Building Adapter: Towards Quickly Applying Building Analytics at Scale. BuildSys 2015: 123-132 - [c21]Asif Salekin, Hongning Wang, John A. Stankovic:
Demo: KinVocal: Detecting Agitated Vocal Events. SenSys 2015: 459-460 - 2014
- [c20]Hongning Wang, Yang Song, Ming-Wei Chang, Xiaodong He, Ahmed Hassan Awadallah, Ryen W. White:
Modeling action-level satisfaction for search task satisfaction prediction. SIGIR 2014: 123-132 - [c19]Yanen Li, Anlei Dong, Hongning Wang, Hongbo Deng, Yi Chang, ChengXiang Zhai:
A two-dimensional click model for query auto-completion. SIGIR 2014: 455-464 - [c18]Yang Song, Hongning Wang, Xiaodong He:
Adapting deep RankNet for personalized search. WSDM 2014: 83-92 - [c17]Hongning Wang, ChengXiang Zhai, Feng Liang, Anlei Dong, Yi Chang:
User modeling in search logs via a nonparametric bayesian approach. WSDM 2014: 203-212 - 2013
- [c16]Mianwei Zhou, Hongning Wang, Kevin Chen-Chuan Chang:
Learning to rank from distant supervision: Exploiting noisy redundancy for relational entity search. ICDE 2013: 829-840 - [c15]Hongbo Deng, Jiawei Han, Heng Ji, Hao Li, Yue Lu, Hongning Wang:
Exploring and Inferring User-User Pseudo-Friendship for Sentiment Analysis with Heterogeneous Networks. SDM 2013: 378-386 - [c14]Yuguo Chen, Jiawei Han, Ming Ji, Jialu Liu, Lu Su, Chi Wang, Hongning Wang:
On the Detectability of Node Grouping in Networks. SDM 2013: 713-721 - [c13]Hongning Wang, Xiaodong He, Ming-Wei Chang, Yang Song, Ryen W. White, Wei Chu:
Personalized ranking model adaptation for web search. SIGIR 2013: 323-332 - [c12]Yang Song, Hao Ma, Hongning Wang, Kuansan Wang:
Exploring and exploiting user search behavior on mobile and tablet devices to improve search relevance. WWW 2013: 1201-1212 - [c11]Hongning Wang, Yang Song, Ming-Wei Chang, Xiaodong He, Ryen W. White, Wei Chu:
Learning to extract cross-session search tasks. WWW 2013: 1353-1364 - [c10]Hongning Wang, ChengXiang Zhai, Anlei Dong, Yi Chang:
Content-aware click modeling. WWW 2013: 1365-1376 - [c9]Ryen W. White, Wei Chu, Ahmed Hassan Awadallah, Xiaodong He, Yang Song, Hongning Wang:
Enhancing personalized search by mining and modeling task behavior. WWW 2013: 1411-1420 - 2012
- [c8]Yue Lu, Hongning Wang, ChengXiang Zhai, Dan Roth:
Unsupervised discovery of opposing opinion networks from forum discussions. CIKM 2012: 1642-1646 - [c7]Hongning Wang, Anlei Dong, Lihong Li, Yi Chang, Evgeniy Gabrilovich:
Joint relevance and freshness learning from clickthroughs for news search. WWW 2012: 579-588 - 2011
- [c6]Hongning Wang, Duo Zhang, ChengXiang Zhai:
Structural Topic Model for Latent Topical Structure Analysis. ACL 2011: 1526-1535 - [c5]Hongning Wang, Yue Lu, ChengXiang Zhai:
Latent aspect rating analysis without aspect keyword supervision. KDD 2011: 618-626 - [c4]Hongning Wang, Chi Wang, ChengXiang Zhai, Jiawei Han:
Learning online discussion structures by conditional random fields. SIGIR 2011: 435-444 - 2010
- [c3]Yue Lu, Huizhong Duan, Hongning Wang, ChengXiang Zhai:
Exploiting Structured Ontology to Organize Scattered Online Opinions. COLING 2010: 734-742 - [c2]Hongning Wang, Yue Lu, Chengxiang Zhai:
Latent aspect rating analysis on review text data: a rating regression approach. KDD 2010: 783-792 - 2008
- [c1]Hongning Wang, Minlie Huang, Xiaoyan Zhu:
A Generative Probabilistic Model for Multi-label Classification. ICDM 2008: 628-637
Editorship
- 2024
- [e1]Grace Hui Yang, Hongning Wang, Sam Han, Claudia Hauff, Guido Zuccon, Yi Zhang:
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024, Washington DC, USA, July 14-18, 2024. ACM 2024 [contents]
Informal and Other Publications
- 2024
- [i84]Anat Hashavit, Tamar Stern, Hongning Wang, Sarit Kraus:
The Impact of Snippet Reliability on Misinformation in Online Health Search. CoRR abs/2401.15720 (2024) - [i83]Haozhe Ji, Cheng Lu, Yilin Niu, Pei Ke, Hongning Wang, Jun Zhu, Jie Tang, Minlie Huang:
Towards Efficient and Exact Optimization of Language Model Alignment. CoRR abs/2402.00856 (2024) - [i82]Jian Guan, Wei Wu, Zujie Wen, Peng Xu, Hongning Wang, Minlie Huang:
AMOR: A Recipe for Building Adaptable Modular Knowledge Agents Through Process Feedback. CoRR abs/2402.01469 (2024) - [i81]Zhepei Wei, Chuanhao Li, Tianze Ren, Haifeng Xu, Hongning Wang:
Incentivized Truthful Communication for Federated Bandits. CoRR abs/2402.04485 (2024) - [i80]Zhiwei Wang, Huazheng Wang, Hongning Wang:
Stealthy Adversarial Attacks on Stochastic Multi-Armed Bandits. CoRR abs/2402.13487 (2024) - [i79]Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu:
Human vs. Generative AI in Content Creation Competition: Symbiosis or Conflict? CoRR abs/2402.15467 (2024) - [i78]Zhexin Zhang, Yida Lu, Jingyuan Ma, Di Zhang, Rui Li, Pei Ke, Hao Sun, Lei Sha, Zhifang Sui, Hongning Wang, Minlie Huang:
ShieldLM: Empowering LLMs as Aligned, Customizable and Explainable Safety Detectors. CoRR abs/2402.16444 (2024) - [i77]Ethan Blaser, Chuanhao Li, Hongning Wang:
Federated Linear Contextual Bandits with Heterogeneous Clients. CoRR abs/2403.00116 (2024) - [i76]Xiaoying Zhang, Jean-Francois Ton, Wei Shen, Hongning Wang, Yang Liu:
Overcoming Reward Overoptimization via Adversarial Policy Optimization with Lightweight Uncertainty Estimation. CoRR abs/2403.05171 (2024) - [i75]Zhenyu Hou, Yilin Niu, Zhengxiao Du, Xiaohan Zhang, Xiao Liu, Aohan Zeng, Qinkai Zheng, Minlie Huang, Hongning Wang, Jie Tang, Yuxiao Dong:
ChatGLM-RLHF: Practices of Aligning Large Language Models with Human Feedback. CoRR abs/2404.00934 (2024) - [i74]Fan Yao, Yiming Liao, Mingzhe Wu, Chuanhao Li, Yan Zhu, James Yang, Qifan Wang, Haifeng Xu, Hongning Wang:
User Welfare Optimization in Recommender Systems with Competing Content Creators. CoRR abs/2404.18319 (2024) - [i73]Zhendong Chu, Zichao Wang, Ruiyi Zhang, Yangfeng Ji, Hongning Wang, Tong Sun:
Improve Temporal Awareness of LLMs for Sequential Recommendation. CoRR abs/2405.02778 (2024) - [i72]Kai Zheng, Haijun Zhao, Rui Huang, Beichuan Zhang, Na Mou, Yanan Niu, Yang Song, Hongning Wang, Kun Gai:
Full Stage Learning to Rank: A Unified Framework for Multi-Stage Systems. CoRR abs/2405.04844 (2024) - [i71]Jiaxin Wen, Ruiqi Zhong, Pei Ke, Zhihong Shao, Hongning Wang, Minlie Huang:
Learning Task Decomposition to Assist Humans in Competitive Programming. CoRR abs/2406.04604 (2024) - [i70]Shangqing Tu, Zhuoran Pan, Wenxuan Wang, Zhexin Zhang, Yuliang Sun, Jifan Yu, Hongning Wang, Lei Hou, Juanzi Li:
Knowledge-to-Jailbreak: One Knowledge Point Worth One Attack. CoRR abs/2406.11682 (2024) - [i69]Aohan Zeng, Bin Xu, Bowen Wang, Chenhui Zhang, Da Yin, Diego Rojas, Guanyu Feng, Hanlin Zhao, Hanyu Lai, Hao Yu, Hongning Wang, Jiadai Sun, Jiajie Zhang, Jiale Cheng, Jiayi Gui, Jie Tang, Jing Zhang, Juanzi Li, Lei Zhao, Lindong Wu, Lucen Zhong, Mingdao Liu, Minlie Huang, Peng Zhang, Qinkai Zheng, Rui Lu, Shuaiqi Duan, Shudan Zhang, Shulin Cao, Shuxun Yang, Weng Lam Tam, Wenyi Zhao, Xiao Liu, Xiao Xia, Xiaohan Zhang, Xiaotao Gu, Xin Lv, Xinghan Liu, Xinyi Liu, Xinyue Yang, Xixuan Song, Xunkai Zhang, Yifan An, Yifan Xu, Yilin Niu, Yuantao Yang, Yueyan Li, Yushi Bai, Yuxiao Dong, Zehan Qi, Zhaoyu Wang, Zhen Yang, Zhengxiao Du, Zhenyu Hou, Zihan Wang:
ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools. CoRR abs/2406.12793 (2024) - [i68]Jiale Cheng, Yida Lu, Xiaotao Gu, Pei Ke, Xiao Liu, Yuxiao Dong, Hongning Wang, Jie Tang, Minlie Huang:
AutoDetect: Towards a Unified Framework for Automated Weakness Detection in Large Language Models. CoRR abs/2406.16714 (2024) - [i67]Zhexin Zhang, Junxiao Yang, Pei Ke, Shiyao Cui, Chujie Zheng, Hongning Wang, Minlie Huang:
Safe Unlearning: A Surprisingly Effective and Generalizable Solution to Defend Against Jailbreak Attacks. CoRR abs/2407.02855 (2024) - [i66]Bosi Wen, Pei Ke, Xiaotao Gu, Lindong Wu, Hao Huang, Jinfeng Zhou, Wenchuang Li, Binxin Hu, Wendy Gao, Jiaxin Xu, Yiming Liu, Jie Tang, Hongning Wang, Minlie Huang:
Benchmarking Complex Instruction-Following with Multiple Constraints Composition. CoRR abs/2407.03978 (2024) - [i65]Jiayi Gui, Yiming Liu, Jiale Cheng, Xiaotao Gu, Xiao Liu, Hongning Wang, Yuxiao Dong, Jie Tang, Minlie Huang:
LogicGame: Benchmarking Rule-Based Reasoning Abilities of Large Language Models. CoRR abs/2408.15778 (2024) - [i64]Jiaxin Wen, Jian Guan, Hongning Wang, Wei Wu, Minlie Huang:
CodePlan: Unlocking Reasoning Potential in Large Langauge Models by Scaling Code-form Planning. CoRR abs/2409.12452 (2024) - [i63]Yuxian Gu, Li Dong, Hongning Wang, Yaru Hao, Qingxiu Dong, Furu Wei, Minlie Huang:
Data Selection via Optimal Control for Language Models. CoRR abs/2410.07064 (2024) - [i62]Qi Liu, Kai Zheng, Rui Huang, Wuchao Li, Kuo Cai, Yuan Chai, Yanan Niu, Yiqun Hui, Bing Han, Na Mou, Hongning Wang, Wentian Bao, Yunen Yu, Guorui Zhou, Han Li, Yang Song, Defu Lian, Kun Gai:
RecFlow: An Industrial Full Flow Recommendation Dataset. CoRR abs/2410.20868 (2024) - [i61]Fan Yao, Yiming Liao, Jingzhou Liu, Shaoliang Nie, Qifan Wang, Haifeng Xu, Hongning Wang:
Unveiling User Satisfaction and Creator Productivity Trade-Offs in Recommendation Platforms. CoRR abs/2410.23683 (2024) - 2023
- [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
- [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
- [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 D. 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
- [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) - 2019
- [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, Hongning Wang:
Factorization Bandits for Online Influence Maximization. CoRR abs/1906.03737 (2019) - [i9]Huazheng Wang, Sonwoo Kim, Eric McCord-Snook, Qingyun Wu, Hongning Wang:
Variance Reduction in Gradient Exploration for Online Learning to Rank. CoRR abs/1906.03766 (2019) - [i8]Huazheng Wang, Zhe Gan, Xiaodong Liu, Jingjing Liu, Jianfeng Gao, Hongning Wang:
Adversarial Domain Adaptation for Machine Reading Comprehension. CoRR abs/1908.09209 (2019) - [i7]Yiling Jia, Nipun Batra, Hongning Wang, Kamin Whitehouse:
Active Collaborative Sensing for Energy Breakdown. CoRR abs/1909.00525 (2019) - [i6]Nan Wang, Hongning Wang:
BPMR: Bayesian Probabilistic Multivariate Ranking. CoRR abs/1909.08737 (2019) - [i5]Xueying Bai, Jian Guan, Hongning Wang:
Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation. CoRR abs/1911.03845 (2019) - [i4]Lin Gong, Lu Lin, Weihao Song, Hongning Wang:
JNET: Learning User Representations via Joint Network Embedding and Topic Embedding. CoRR abs/1912.00465 (2019) - 2018
- [i3]Huazheng Wang, Ramsey Langley, Sonwoo Kim, Eric McCord-Snook, Hongning Wang:
Efficient Exploration of Gradient Space for Online Learning to Rank. CoRR abs/1805.07317 (2018) - [i2]Qingyun Wu, Naveen Iyer, Hongning Wang:
Learning Contextual Bandits in a Non-stationary Environment. CoRR abs/1805.09365 (2018) - [i1]Nan Wang, Hongning Wang, Yiling Jia, Yue Yin:
Explainable Recommendation via Multi-Task Learning in Opinionated Text Data. CoRR abs/1806.03568 (2018)
Coauthor Index
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