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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)- [c114]Chuanhao Li, Huazheng Wang, Mengdi Wang, Hongning Wang:
Learning Kernelized Contextual Bandits in a Distributed and Asynchronous Environment. ICLR 2023 - [c113]Lu Lin, Jinghui Chen, Hongning Wang:
Spectral Augmentation for Self-Supervised Learning on Graphs. ICLR 2023 - [c112]Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu:
How Bad is Top-K Recommendation under Competing Content Creators? ICML 2023: 39674-39701 - [c111]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 - [c110]Huazheng Wang, Haifeng Xu, Chuanhao Li, Zhiyuan Liu, Hongning Wang:
Incentivizing Exploration in Linear Contextual Bandits under Information Gap. RecSys 2023: 415-425 - [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 - [i54]Xiaoying Zhang, Hongning Wang, Hang Li:
Disentangled Representation for Diversified Recommendations. CoRR abs/2301.05492 (2023) - [i53]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) - [i52]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) - [i51]Zhendong Chu, Hongning Wang:
Meta-Reinforcement Learning via Exploratory Task Clustering. CoRR abs/2302.07958 (2023) - [i50]Xiaoying Zhang, Junpu Chen, Hongning Wang, Hong Xie, Hang Li:
Uncertainty-Aware Off-Policy Learning. CoRR abs/2303.06389 (2023) - [i49]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) - 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, 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
- [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@SenSys 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]