Publications

Patents and Defensive Publications

• Spatio-temporal graph neural network for time series prediction
  Swati Sharma, Srinivasan Iyengar, Kshitij KAPOOR, Shun ZHENG, Wei Cao, Jiang Bian, Shivkumar Kalyanaraman, and John Patrick Lemmon
  US Patent pending by Microsoft (2022)

• Image super-resolution reconstructing
  Shuxin ZHENG, Chang Liu, Di He, Guolin Ke, Jiang Bian, and Tie-Yan Liu
  US Patent (US20230206396A1) pending by Microsoft (2020)

• Image rescaling
  Shuxin ZHENG, Chang Liu, Di He, Guolin Ke, Yatao Li, Jiang Bian, and Tie-Yan Liu
  US Patent (US20230093734A1) pending by Microsoft (2020)

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• Trend Prediction Based on Neural Network
  Weiqing Liu, Jiang Bian, and Tie-Yan Liu
  US Patent pending by Microsoft (2018)

• Recurrent GBDT for Multivariate Multi-Step Time-Series Forecasting
  Guolin Ke, Jiang Bian, and Tie-Yan Liu
  US Patent pending by Microsoft (2018)

• Inventory Control of Resources
  Jia Zhang, Weidong Ma, Jiang Bian, and Tie-Yan Liu
  US Patent pending by Microsoft (2018)

• Graph-Based Ranking Of Items
  Jiang Bian, Taifeng Wang, and Tie-Yan Liu
  US Patent US20150120432 A1 (Publication date: Apr 30, 2015) (2015)

• Method or System for Content Recommendations
  Anlei Dong, Jiang Bian, Xiaofeng He, Srihari Reddy, and Yi Chang
  US Patent US20130179252 A1 (Publication date: Jul 11, 2013)

• Ranking Specialization for A Search
  Jiang Bian, Xin Li, Fan Li, Zhaohui Zheng, and Hongyuan Zha
  US Patent US20120011112 A1 (Publication date: Jan 12, 2012)

• A Method of Using a Pairwise Learning Model in an Online Recommendation System
  Jiang Bian, Bo Long, Lihong Li, Taesup Moon, Anlei Dong, and Yi Chang
  IP.com Prior Art Database Disclosure (Source: IPCOM), Disclosure Number IPCOM000216302D dated 29-Mar-2012

• Method for Classifying Local Search Queries by Analyzing Local Query Logs
  Jiang Bian and Yi Chang
  IP.com Prior Art Database Disclosure (Source: IPCOM), Disclosure Number IPCOM000211501D dated 07-Oct-2011

Book Chapters

• Relevance Ranking for Vertical Search Engines
  Bo Long, Yi Chang
  Morgan Kaufmann, 2014

Journals

• Rapid Inference of Nitrogen Oxide Emissions Based on a Top-Down Method with a Physically Informed Variational Autoencoder (pdf)
  Jia Xing, Siwei Li, Shuxin Zheng, Chang Liu, Xiaochun Wang, Lin Huang, Ge Song, Yihan He, Shuxiao Wang, Shovan Kumar Sahu, Jia Zhang, Jiang Bian, Yun Zhu, Tie-Yan Liu, and Jiming Hao.
  Environmental Science & Technology (EST), Volume 56, Issue 14, Page 9903-9914, July 6th, 2022, DOI: 10.1021/acs.est.1c08337

• Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States (pdf)
  Estee Y. Cramer, et al.
  Proceedings of the National Academy of Sciences (PNAS), Volume 119, No 15, e2113561119, April 8th 2022, DOI: 10.1073/pnas.2113561119

• Mimicking atmospheric photochemical modeling with a deep neural network (pdf)
  Jia Xing, et al.
  Atmospheric Research (AR), Volume 265, Jan 2022, DOI: 10.1016/j.atmosres.2021.105919

• Model complexity of deep learning: a survey (pdf)
  Xia Hu, Lingyang Chu, Jian Pei, Weiqing Liu, and Jiang Bian
  Knowledge and Information Systems (KIS), Volume 63, Pages 2585–2619, August 2021, DOI: 10.1007/s10115-021-01605-0

• Demonstration Actor Critic (pdf)
  Guoqing Liu, Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin, Nenghai Yu, and Tie-Yan Liu
  Neurocomputing (NEUCOM), Volume 434, 28 April 2021, Pages 194-202, DOI: 10.1016/j.neucom.2020.12.116

• Deep Subdomain Adaptation Network for Image Classification (pdf)
  Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Guolin Ke, Jingwu Chen, Jiang Bian, Hui Xiong, and Qing He
  IEEE Transactions on Neural Networks and Learning Systems  (TNNLS), Vol. ??, No. ??, May 2020 

• Semi-supervised Neural Machine Translation via Marginal Distribution Estimation (pdf)
  Yijun Wang, Yingce Xia, Li Zhao, Jiang Bian, Tao Qin, En-Hong Chen, and Tie-Yan Liu
  IEEE Transactions on Audio, Speech and Language Processing (TASLP), Vol. 27, No. 10, October 2019 

• KNET: A General Framework for Learning Word Embedding using Morphological Knowledge (pdf)
  Qing Cui, Bin Gao, Jiang Bian, and Tie-Yan Liu
  ACM Transactions on Information Systems (TOIS), Vol. 34, No. 1, Article 4, August 2015

• Active Learning for Ranking through Expected Loss Optimization (pdf)
  Bo Long, Jiang Bian, Olivier Chapelle, Ya Zhang, Yoshiyuki Inagaki, and Yi Chang
  IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 27, No. 5, May 2015

• Indexing Earth Mover's Distance over Network Metrics (pdf)
  Ting Wang, Shicong Meng, and Jiang Bian
  IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 27, No. 6, June 2015

• Exploiting User Preference for Online Learning in Web Content Optimization Systems (pdf)
  Jiang Bian, Bo Long, Lihong Li, Taesup Moon, Anlei Dong, and Yi Chang
  ACM Transactions on Intelligent Systems and Technology (TIST), Special Issue on Linking Social Granularity and Functions, Volume 5 Issue 2, April 2014

• User Action Interpretation for Online Content Optimization (pdf)
  Jiang Bian, Anlei Dong, Xiaofeng He, Srihari Reddy, and Yi Chang
  IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume 25, Issue 9, DOI: 10.1109/TKDE.2012.130, September 2013, Pages 2161–2174

• Learning to Blend Vitality Rankings from Heterogeneous Social Networks (pdf)
  Jiang Bian, Yi Chang, Yun Fu, and Wen-Yen Chen
  Neurocomputing (NEUCOM), Volume 97, 15 November 2012, Pages 390–397, DOI: 10.1016/j.neucom.2012.06.024

• Modeling Information Seeker Satisfaction in Community Question Answering (pdf)
  Eugene Agichtein, Yandong Liu, and Jiang Bian
  ACM Transactions on Knowledge Discovery from Data (TKDD), special Issue on Social Computing, Behavioral Modeling, and Prediction, 2009

Referred Conference Publications

• BatteryML:An Open-source platform for Machine Learning on Battery Degradation, (pdf)
  Han Zhang, Xiaofan Gui, Shun Zheng, Ziheng Lu, Yuqi Li,  and Jiang Bian.
  The 12th International Conference on Learning Representations, Kigali Rwanda (ICLR2024)

• Whittle Index with Multiple Actions and State Constraint for Inventory Management, (pdf)
  Chuheng Zhang, Xiangsen Wang, Wei Jiang, Xianliang Yang, Siwei Wang, Lei Song, and Jiang Bian.
  The 12th International Conference on Learning Representations, Kigali Rwanda (ICLR2024)

• MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process, (pdf)
  Xinyao Fan, Yueying Wu, Chang Xu, Yuhao Huang, Weiqing Liu, and Jiang Bian .
  The 12th International Conference on Learning Representations, Kigali Rwanda (ICLR2024)

• GAIA: Data-driven Zero-shot Talking Avatar Generation, (pdf)
  Tianyu He, Junliang Guo, Runyi Yu, Yuchi Wang, jialiang zhu, Kaikai An, Leyi Li, Xu Tan, Chunyu Wang, Han Hu, HsiangTao Wu, sheng zhao, and Jiang Bian .
  The 12th International Conference on Learning Representations, Kigali Rwanda (ICLR2024)

• Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers, (pdf)
  Qingyan Guo, Rui Wang, Junliang Guo, Bei Li, Kaitao Song, Xu Tan, Guoqing Liu, Jiang Bian, and Yujiu Yang.
  The 12th International Conference on Learning Representations, Kigali Rwanda (ICLR2024)

• Learning Pareto-Optimal Policies for Multi-Objective Joint Distribution, (pdf)
  Xin-Qiang Cai, Pushi Zhang, Li Zhao, Jiang Bian, Masashi Sugiyama, and Ashley Juan Llorens
  The 37th Conference on Neural Information Processing Systems, New Orleans, LA, US (NeurIPS2023)

• On the Generalization Properties of Diffusion Models, (pdf)
  Puheng Li, Zhong Li, Huishuai Zhang, Jiang Bian
  The 37th Conference on Neural Information Processing Systems, New Orleans, LA, US (NeurIPS2023)

• Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series, (pdf)
  Jiawen Zhang, Shun Zheng, Wei Cao, Jiang Bian and Jia Li.
  The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, CA, US (KDD2023)

• Web-based Long-term Spine Treatment Outcome Forecasting, (pdf)
  Hangting Ye, Zhining Liu, Wei Cao, Amir M. Amiri, Jiang Bian, Yi Chang, Jon D. Lurie, Jim Weinstein, and Tie-Yan Liu.
  The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, CA, US (KDD2023)

• Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance, (pdf)
  Yuchen Fang, Zhenggang Tang, Kan Ren, Weiqing Liu, Li Zhao, Jiang Bian, Dongsheng Li, Weinan Zhang, Yong Yu, and Tie-Yan Liu.
  The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, CA, US (KDD2023)

• Removing Camouflage and Revealing Collusion: Leveraging Gang-crime Pattern in Fraudster Detection, (pdf)
  Lewen Wang, Haozhe Zhao, Cunguang Feng, Weiqing Liu, Congrui Huang, Marco Santoni, Manuel Cristofaro, Paola Jafrancesco, and Jiang Bian.
  The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, CA, US (KDD2023)

• H-TSP: Hierarchically Solving the Large-Scale Traveling Salesman P, (pdf)
  Xuanhao Pan, Yan Jin, Yuandong Ding, Mingxiao Feng, Li Zhao, Lei Song, and Jiang Bian.
  The 37th AAAI Conference on Artificial Intelligence, Washington DC, US (AAAI2023)

• Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problem, (pdf)
  Yan Jin, Yuandong Ding, Xuanhao Pan, Kun He, Li Zhao, Tao Qin, Lei Song, and Jiang Bian.
  The 37th AAAI Conference on Artificial Intelligence, Washington DC, US (AAAI2023)

• Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping, (pdf)
  Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, and Jiang Bian.
  The 11th International Conference on Learning Representations, Kigali Rwanda (ICLR2023)

• UADB: Unsupervised Anomaly Detection Booster, (pdf)
  Hangting Ye, Zhining Liu, Xinyi Shen, Wei Cao, Shun Zheng, Xiaofan Gui, Huishuai Zhang, Yi Chang, and Jiang Bian
  2023 IEEE 39th International Conference on Data Engineering, Anaheim, CA, US (ICDE2023)

• Learning physics-informed neural networks without stacked back-propagation, (pdf)
  Di He, Shanda Li, Wenlei Shi, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, and Tie-Yan Liu.
  The 26th International Conference on Artificial Intelligence and Statistics, Valencia, Spain (AISTAT2023)

• Curriculum Offline Reinforcement Learning, (pdf)
  Yuanying Cai, Chuheng Zhang, Hanye Zhao, Li Zhao, and Jiang Bian.
  The 22nd International Conference on Autonomous Agents and Multiagent Systems, London, UK (AAMAS2023)

• TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets, (pdf)
  Yuanying Cai, Chuheng Zhang, Li Zhao, Wei Shen, Xuyun Zhang, Lei Song, Jiang Bian, Tao Qin, and Tie-Yan Liu.
  2022 IEEE International Conference on Data Mining, Orlando, FL, US (ICDM2022)

• Efficient and Effective Multi-task Grouping via Meta Learning on Task Combinations, (pdf)
  Xiaozhuang Song, Shun Zheng, Wei Cao, James Yu, and Jiang Bian
  The 36th Conference on Neural Information Processing Systems, New Orleans, LA, US (NeurIPS2022)

• The CityLearn Challenge 2022: Overview, Results, and Lessons Learned, (pdf)
  Xiaozhuang Song, Han Zhang, Xiaoning Dong, Shun Zheng, Jiang Bian, et al.
  The 36th Conference on Neural Information Processing Systems, New Orleans, LA, US (NeurIPS2022)

• A Continuous Glucose Monitoring Measurements Forecasting Approach via Sporadic Blood Glucose Monitoring, (pdf)
  Yuting Xing, Hangting Ye, Xiaoyu Zhang, Wei Cao, Shun Zheng, Jiang Bian, and Yike Guo.
  IEEE International Conference on Bioinformatics and Biomedicine, Las Vegas, NV, US (BIBM2022)

• A Graph-based Spatiotemporal Model for Energy Markets, (pdf)
  Swati Sharma, Srinivasan Iyengar, Shun Zheng, Kshitij Kapoor, Wei Cao, Jiang Bian, Shivkumar Kalyanaraman, and John Lemmon.
  The 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, US (CIKM2022)

• KGE-CL: Contrastive Learning of Tensor Decomposition Based Knowledge Graph Embeddings, (pdf)
  Zhiping Luo, Wentao Xu, Weiqing Liu, Jiang Bian, Jian Yin, and Tie-Yan Liu.
  The 29th International Conference on Computational Linguistics, Gyeongju, Korea (COLING2022)

• Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble, (pdf)
  Zhengyu Yang, Kan Ren, Xufang Luo, Minghuan Liu, Weiqing Liu, Jiang Bian, Weinan Zhang, and Dongsheng Li.
  The 31st International Joint Conference on Artificial Intelligence, Montreal, CA (IJCAI2022)

• Learning Differential Operators for Interpretable Time Series Modeling, (pdf)
  Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, and Jiang Bian.
  The 28th ACM SIGKDD Conference on Knowledge, Discovery, and Data Mining, DC, US (KDD2022)

• DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting, (pdf)
  Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, and Tie-Yan Liu.
  The 10th International Conference on Learning Representations, Virtual (ICLR2022)

• Multi-Granularity Residual Learning with Confidence Estimation for Time Series Prediction, (pdf)
  Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, and Jiang Bian.
  The 31st The Web Conference, Lyon, France (WWW2022)

• DDG-DA: Data Distribution Generation for Predictable ConceptDrift Adaptation, (pdf)
  Wendi Li, Xiao Yang, Weiqing Liu, Yingce Xia, and Jiang Bian.
  The 36th AAAI Conference on Artificial Intelligence, Vancouver, CA (AAAI2022)

• Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion, (pdf)
  Min Hou, Chang Xu, Yang Liu, Weiqing Liu, Jiang Bian, Le Wu, Zhi Li, Enhong Chen, and Tie-Yan Liu.
  The 30th ACM International Conference on Information and Knowledge Management, Gold Coast, Queensland, Australia (CIKM2021)

• HierST: A Unified Hierarchical Spatial-temporal Framework for COVID-19 Trend Forecasting, (pdf)
  Shun Zheng, Zhifeng Gao, Wei Cao, Jiang Bian, and Tie-Yan Liu.
  The 30th ACM International Conference on Information and Knowledge Management, Gold Coast, Queensland, Australia (CIKM2021)

• Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport, (pdf)
  Hengxu Lin, Dong Zhou, Weiqing Liu, and Jiang Bian.
  The 27th ACM SIGKDD Conference on Knowledge, Discovery, and Data Mining, Singapore (KDD2021)

• Revisiting the Evaluation of End-to-end Event Extraction, (pdf)
  Shun Zheng, Wei Cao, Wei Xu, and Jiang Bian.
  The 59th Annual Meeting of the Association for Computational Linguistics, Bangkok, Thailand (ACL2021)

• Independence-aware Advantage Estimation, (pdf)(video)
  Pushi Zhang, Li Zhao, Guoqing Liu, Jiang Bian, Minlie Huang, Tao Qin, and Tie-Yan Liu.
  The 30th International Joint Conference on Artificial Intelligence, Montreal, CA (IJCAI2021)

• REST: Relational Event-driven Stock Trend Forecasting, (pdf)(video)
  Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, and Tie-Yan Liu
  The 30th The Web Conference, Ljubljana, Slovenia (WWW2021)

• Universal Trading for Order Execution with Oracle Policy Distillation, (pdf)
  Yuchen Fang, Kan Ren, Weiqing Liu, Dong Zhou, Weinan Zhang, Jiang Bian, Yong Yu, and Tie-Yan Liu
  The 35th AAAI Conference on Artificial Intelligence, Vancouver, CA (AAAI2021)

• Learning to Reweight with Deep Interactions, (pdf)
  Yang Fan, Yingce Xia, Lijun Wu, Shufang Xie, Weiqing Liu, Jiang Bian, Xiangyang Li, and Tao Qin
  The 35th AAAI Conference on Artificial Intelligence, Vancouver, CA (AAAI2021)

• Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations, (pdf)
  Wenlei Shi, Xinran Wei, Jia Zhang, Xiaoyuan Ni, Arthur Jiang, Jiang Bian, and Tie-Yan Liu
  The 20th International Conference on Autonomous Agents and Multiagent Systems, Montreal, CA (AAMAS2021)

• Invertible Image Rescaling, (pdf)
  Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, and Tie-Yan Liu
  The 16th European Conference on Computer Vision, Glasgow, UK (ECCV2020)

• MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler, (pdf)
  Zhining Liu, Pengfei Wei, Jing Jiang, Wei Cao, Jiang Bian, Yi Chang
  The 34th Conference on Neural Information Processing Systems, Vancouver Canada (NeurIPS2020)

• Measuring Model Complexity of Neural Networks with Curve Activation Functions, (pdf)
  Xia Hu, Weiqing Liu, Jiang Bian, and Jian Pei
  The 26th ACM SIGKDD Conference on Knowledge, Discovery, and Data Mining, San Diego, CA, US (KDD2020)

• Self-paced Ensemble for Highly Imbalanced Massive Data Classification, (pdf)
  Zhining Liu, Wei Cao, Zhifeng Gao, Jiang Bian, Hechang Chen, Yi Chang, and Tie-Yan Liu
  The 36th IEEE International Conference on Data Engineering, Dallas, TX, US (ICDE2020)

• Light Multi-segment Activation for Model Compression, (pdf)
  Zhenhui Xu, Guolin Ke, Jia Zhang, Jiang Bian, and Tie-Yan Liu
  The 34th AAAI Conference on Artificial Intelligence, New York City, NY, US (AAAI2020)

• Fully Parameterized Quantile Function for Distributional Reinforcement Learning, (pdf)
  Derek Yang, Li Zhao, Zichuan Lin, Jiang Bian, Tao Qin, and Tie-Yan Liu
  The 33rd Conference on Neural Information Processing Systems, Vancouver Canada (NeurIPS2019)

• Unified Policy Optimization for Robust Reinforcement Learning, (pdf)
  Zichuan Lin, Li Zhao, Jiang Bian, Tao Qin, and Guangwen Yang
  The 11th Asian Conference on Machine Learning, Nagoya, Japan (ACML2019)

• Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction, (pdf)
  Shun Zheng, Wei Cao, Wei Xu, and Jiang Bian
  2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Hong Kong, China (EMNLP-IJCNLP2019)

• DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks, (pdf)
  Guolin Ke, Zhenhui Xu, Jia Zhang, Jiang Bian, and Tie-Yan Liu
  The 25th ACM SIGKDD Conference on Knowledge, Discovery, and Data Mining, Anchorage, AK, US (KDD2019)

• Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding, (pdf)
  Zhige Li, Derek Yang, Li Zhao, Jiang Bian, Tao Qin, and Tie-Yan Liu
  The 25th ACM SIGKDD Conference on Knowledge, Discovery, and Data Mining, Anchorage, AK, US (KDD2019)

• Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction, (pdf)
  Chi Chen, Li Zhao, Jiang Bian, Chunxiao Xing, and Tie-Yan Liu
  The 25th ACM SIGKDD Conference on Knowledge, Discovery, and Data Mining, Anchorage, AK, US (KDD2019)

• A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics Network, (pdf)
  Xihan Li, Jia Zhang, Jiang Bian, Yunhai Tong, and Tie-Yan Liu
  The 18th International Conference on Autonomous Agents and Multiagent Systems, Montreal, CA (AAMAS2019)

• Trust Region Evolution Strategies, (pdf)
  Guoqing Liu, Li Zhao, Feidiao Yang, Jiang Bian, Tao Qin, Nenghai Yu, and Tie-Yan Liu
  The 33rd AAAI Conference on Artificial Intelligence, Honolulu, HI, US (AAAI2019)

• Investor-Imitator: A Framework for Trading Knowledge Extraction, (pdf)
  Yi Ding, Weiqing Liu, Jiang Bian, Daoqiang Zhang, and Tie-Yan Liu
  The 24th ACM SIGKDD Conference on Knowledge, Discovery, and Data Mining, London, UK (KDD2018)

• Slim-DP: A Multi-Agent System for Communication-Efficient Distributed Deep Learning, (pdf)
  Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, and Tie-Yan Liu
  The 17th International Conference on Autonomous Agents and Multiagent Systems, Stockholm, Sweden (AAMAS2018)

• Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction, (pdf)
  Ziniu Hu, Weiqing Liu, Jiang Bian, Xuanzhe Liu, and Tie-Yan Liu
  The 11th ACM International Conference on Web Search and Data Mining, Los Angeles, CA, US (WSDM2018)

• Dual Transfer Learning for Neural Machine Translation with Marginal Distribution Regularization, (pdf)
  Yijun Wang, Yingce Xia, Li Zhao, Jiang Bian, Tao Qin, GuiQuan liu, and Tie-Yan Liu
  The 32th AAAI Conference on Artificial Intelligence, New Orleans, LA, USA (AAAI2018)

• Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks, (pdf)
  Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu and Tie-Yan Liu
  The 10th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Skopje, Macedonia (ECML/PKDD2017)

• Dual Supervised Learning, (pdf)
  Yingce Xia, Tao Qin, Wei Chen, Jiang Bian, Nenghai Yu and Tie-Yan Liu
  The 34th International Conference on Machine Learning, Sydney, Australia (ICML2017)

• Dual Inference for Machine Learning, (pdf)
  Yingce Xia, Jiang Bian, Tao Qin, Nenghai Yu and Tie-Yan Liu
  The 26th International Joint Conference on Artificial Intelligence, Melbourne, Australia (IJCAI2017)

• Solving Verbal Questions in IQ Test by Knowledge-Powered Word Embedding, (pdf)
  Huazheng Wang, Fei Tian, Bin Gao, Chengjieren Zhu, Jiang Bian, and Tie-Yan Liu
  The 2016 Conference on Empirical Methods in Natural Language Processing, Austin, Texas (EMNLP2016)

• RC-NET: A General Framework for Incorporating Knowledge into Word Representations, (pdf)
  Chang Xu, Yalong Bai, Jiang Bian, Bin Gao, Gang Wang, Xiaoguang Liu, and Tie-Yan Liu
  The 23rd ACM International Conference on Information and Knowledge Management, Shanghai, China (CIKM2014)

• WordRep: A Benchmark for Research on Learning Word Representations, (pdf)(Download Dataset)
  Bin Gao, Jiang Bian, and Tie-Yan Liu
  ICML 2014 Workshop on Knowledge-Powered Deep Learning for Text Mining, Beijing, China (KPDLTM2014)

• Knowledge-Powered Deep Learning for Word Embedding, (pdf)
  Jiang Bian, Bin Gao, and Tie-Yan Liu
  The 7th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Nancy, France(ECML/PKDD2014)

• A Scalable Probabilistic Model for Learning Multi-Prototype Word Embeddings, (pdf)
  Fei Tian, Jiang Bian, Bin Gao, Tie-Yan Liu, Hanjun Dai, and Rui Zhang
  The 25th International Conference on Computational Linguistics, Dublin, Ireland(COLING2014)

• Co-learning of Word Representations and Morpheme Representations, (pdf)
  Siyu Qiu, Qing Cui, Jiang Bian, Bin Gao, and Tie-Yan Liu
  The 25th International Conference on Computational Linguistics, Dublin, Ireland(COLING2014)

• Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks, (pdf)
  Yuyu Zhang, Hanjun Dai, Chang Xu, Jun Feng, Taifeng Wang, Jiang Bian, Bin Wang, and Tie-Yan Liu
  The 28th AAAI Conference on Artificial Intelligence, Quebec City, Quebec, Canada (AAAI2014)

• Sampling Dilemma: Towards Effective Data Sampling for Click Prediction in Sponsored Search, (pdf)
  Jun Feng, Jiang Bian, Taifeng Wang, Wei Chen, Xiaoyan Zhu, and Tie-Yan Liu
  The 7th ACM International Conference on Web Search and Data Mining, New York City, NY, US (WSDM2014)

• Psychological Advertising: Exploring User Psychology for Click Prediction in Sponsored Search, (pdf)(video)
  Taifeng Wang, Jiang Bian, Shusen Liu, Yuyu Zhang, and Tie-Yan Liu
  The 19th ACM SIGKDD Conference on Knowledge, Discovery, and Data Mining, Chicago, IL, US (KDD2013)

• An Effective General Framework for Localized Content Optimization, (pdf)
  Yoshiyuki Inagaki, Jiang Bian, and Yi Chang
  The 22th International World Wide Web Conference, Rio de Janeiro, Brazil (WWW2013)

• Enhancing Product Search by Best-Selling Prediction in E-Commerce, (pdf)
  Bo Long, Jiang Bian, Anlei Dong, and Yi Chang
  The 21th ACM International Conference on Information and Knowledge Management, Maui, HI, US (CIKM2012)

• Model News Relatedness through User Comments, (pdf)
  Xuanhui Wang, Jiang Bian, Yi Chang and Belle Tseng
  The 21th International World Wide Web Conference, Lyon, France (WWW2012)

• Optimizing User Exploring Experience in Emerging E-Commerce Products, (pdf)
  Xiubo Geng, Xin Fan, Jiang Bian, Xin Li, Zhongyan Zhang and Zhaohui Zheng
  The 21th International World Wide Web Conference, Lyon, France (WWW2012)

• Learning to Blend Vitality Rankings from Heterogeneous Social, (pdf)
  Jiang Bian, Yun Fu, Wen-yen Chen, and Yi Chang
  Yahoo! Tech Pulse 2011

• A Taxonomy of Local Search: Semi-Supervised Query Classification Driven by Information Needs, (pdf)
  Jiang Bian and Yi Chang
  The 20th ACM International Conference on Information and Knowledge Management, Glasgow, UK (CIKM2011)

• User Action Interpretation for Personalized Content Optimization in Recommender Systems, (pdf)
  Anlei Dong, Jiang Bian, Xiaofeng He, Srihari Reddy, and Yi Chang
  The 20th ACM International Conference on Information and Knowledge Management, Glasgow, UK (CIKM2011)

• Enhancing Mobile Search Using Web Search Log Data, (pdf)
  Yoshiyuki Inagaki, Jiang Bian, Yi Chang, and Motoko Maki
  The 34th Annual International ACM SIGIR Conference, Beijing, China (SIGIR2011)

• Ranking Specialization for Web Search: A Divide-and-Conquer Approach by Using Topical RankSVM, (pdf)
  Jiang Bian, Xin Li, Fan Li, Zhaohui Zheng, and Hongyuan Zha
  The 19th International World Wide Web Conference, Raleigh, NC, US (WWW2010)

• Optimizing Unified Loss for Web Ranking Specialization, (pdf)
  Fan Li, Xin Li, Jiang Bian, and Zhaohui Zheng
  The 19th ACM International Conference on Information and Knowledge Management, Toronto, Canada (CIKM2010)

• Hybrid Generative/Discriminative Learning for Automatic Image Annotation, (pdf)
  Shuanghong Yang, Jiang Bian, and Hongyuan Zha
  The 26th Conference on Uncertainty in Artificial Intelligence, Catalina Island, CA, US (UAI2010)

• Ranking with Query-Dependent Loss for Web Search, (pdf)(video)
  Jiang Bian, Tie-Yan Liu, Tao Qin, and Hongyuan Zha
  The 3rd ACM International Conference on Web Search and Data Mining, New York City, NY, US (WSDM2010)

• Learning to Recognize Reliable Users and Content in Social Media with Coupled Mutual Reinforcement , (pdf)
  Jiang Bian, Yandong Liu, Ding Zhou, Eugene Agichtein, and Hongyuan Zha
  The 18th International World Wide Web Conference, Madrid, Spain (WWW2009)

• Predicting Information Seeker Satisfaction in Community Question Answering, (pdf)
  Yandong Liu, Jiang Bian, and Eugene Agichtein
  The 31st Annual International ACM SIGIR Conference, Singapore (SIGIR2008)

• Finding the Right Facts in the Crowd: Factoid Question Answering over Social Media, (pdf)
  Jiang Bian, Yandong Liu, Eugene Agichtein, and Hongyuan Zha
  The 17th International World Wide Web Conference, Beijing, China (WWW2008)

• Exploring Social Annotations for Information Retrieval, (pdf)
  Ding Zhou, Jiang Bian, Shuyi Zheng, Giles Lee, and Hongyuan Zha
  The 17th International World Wide Web Conference, Beijing, China (WWW2008)

• A Few Bad Votes Too Many? Towards Robust Ranking in Social Media, (pdf)
  Jiang Bian, Yandong Liu, Eugene Agichtein, and Hongyuan Zha
  The 4th International Workshop on Adversarial Information Retrieval on the Web, Beijing, China (AIRWeb2008)