


Остановите войну!
for scientists:
Jiang Bian 0002
Person information

- affiliation: Microsoft Research Asia, Beijing, China
- affiliation (former): Yahoo! Labs, Sunnyvale, CA, USA
- affiliation (PhD 2010): Georgia Institute of Technology, Atlanta, GA, USA
Other persons with the same name
- Jiang Bian — disambiguation page
- Jiang Bian 0001
— University of Florida, Department of Health Outcomes and Biomedical Informatics, Gainesville, FL, USA (and 1 more)
- Jiang Bian 0003
— Baidu Research, Big Data Laboratory, Beijing, China (and 1 more)
- Jiang Bian 0004
— Chinese Academy of Sciences, Institute of Automation, State Key Laboratory for Management and Control of Complex Systems, Beijing, China
- Jiang Bian 0005
— Northwest A&F University, Yangling, China
Refine list

refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2022
- [c56]Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian:
Multi-Granularity Residual Learning with Confidence Estimation for Time Series Prediction. WWW 2022: 112-121 - [i43]Wendi Li, Xiao Yang, Weiqing Liu, Yingce Xia, Jiang Bian:
DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation. CoRR abs/2201.04038 (2022) - [i42]Di He, Wenlei Shi, Shanda Li, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu:
Learning Physics-Informed Neural Networks without Stacked Back-propagation. CoRR abs/2202.09340 (2022) - [i41]Lin Huang, Qiyuan Dong, Lijun Wu, Jia Zhang, Jiang Bian, Tie-Yan Liu:
AF2: Adaptive Focus Framework for Aerial Imagery Segmentation. CoRR abs/2202.10322 (2022) - [i40]Lin Huang, Lijun Wu, Jia Zhang, Jiang Bian, Tie-Yan Liu:
Dynamic Relation Discovery and Utilization in Multi-Entity Time Series Forecasting. CoRR abs/2202.10586 (2022) - [i39]Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu:
DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting. CoRR abs/2203.07681 (2022) - [i38]Zhengyu Yang, Kan Ren, Xufang Luo, Minghuan Liu, Weiqing Liu, Jiang Bian, Weinan Zhang, Dongsheng Li:
Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble. CoRR abs/2205.09284 (2022) - [i37]Wenlei Shi, Xinquan Huang, Xiaotian Gao, Xinran Wei, Jia Zhang, Jiang Bian, Mao Yang, Tie-Yan Liu:
LordNet: Learning to Solve Parametric Partial Differential Equations without Simulated Data. CoRR abs/2206.09418 (2022) - 2021
- [j9]Guoqing Liu, Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin
, Nenghai Yu, Tie-Yan Liu:
Demonstration actor critic. Neurocomputing 434: 194-202 (2021) - [j8]Xia Hu, Lingyang Chu, Jian Pei
, Weiqing Liu, Jiang Bian:
Model complexity of deep learning: a survey. Knowl. Inf. Syst. 63(10): 2585-2619 (2021) - [c55]Yuchen Fang, Kan Ren, Weiqing Liu, Dong Zhou, Weinan Zhang, Jiang Bian, Yong Yu, Tie-Yan Liu:
Universal Trading for Order Execution with Oracle Policy Distillation. AAAI 2021: 107-115 - [c54]Yang Fan, Yingce Xia, Lijun Wu, Shufang Xie, Weiqing Liu, Jiang Bian, Tao Qin, Xiang-Yang Li:
Learning to Reweight with Deep Interactions. AAAI 2021: 7385-7393 - [c53]Shun Zheng, Wei Cao, Wei Xu, Jiang Bian:
Revisiting the Evaluation of End-to-end Event Extraction. ACL/IJCNLP (Findings) 2021: 4609-4617 - [c52]Wenlei Shi, Xinran Wei, Jia Zhang, Xiaoyuan Ni, Arthur Jiang, Jiang Bian, Tie-Yan Liu:
Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations. AAMAS 2021: 1191-1199 - [c51]Min Hou, Chang Xu, Yang Liu, Weiqing Liu, Jiang Bian, Le Wu, Zhi Li, Enhong Chen
, Tie-Yan Liu:
Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion. CIKM 2021: 700-709 - [c50]Shun Zheng, Zhifeng Gao, Wei Cao, Jiang Bian, Tie-Yan Liu:
HierST: A Unified Hierarchical Spatial-temporal Framework for COVID-19 Trend Forecasting. CIKM 2021: 4383-4392 - [c49]Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian:
Deep risk model: a deep learning solution for mining latent risk factors to improve covariance matrix estimation. ICAIF 2021: 12:1-12:8 - [c48]Tianhao Zhang, Qiwei Ye, Jiang Bian, Guangming Xie, Tie-Yan Liu:
MFVFD: A Multi-Agent Q-Learning Approach to Cooperative and Non-Cooperative Tasks. IJCAI 2021: 500-506 - [c47]Pushi Zhang, Li Zhao, Guoqing Liu, Jiang Bian, Minlie Huang, Tao Qin, Tie-Yan Liu:
Independence-aware Advantage Estimation. IJCAI 2021: 3349-3355 - [c46]Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian:
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport. KDD 2021: 1017-1026 - [c45]Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu:
REST: Relational Event-driven Stock Trend Forecasting. WWW 2021: 1-10 - [i36]Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu:
REST: Relational Event-driven Stock Trend Forecasting. CoRR abs/2102.07372 (2021) - [i35]Xia Hu, Lingyang Chu, Jian Pei, Weiqing Liu, Jiang Bian:
Model Complexity of Deep Learning: A Survey. CoRR abs/2103.05127 (2021) - [i34]Yuchen Fang, Kan Ren, Weiqing Liu, Dong Zhou, Weinan Zhang, Jiang Bian, Yong Yu, Tie-Yan Liu:
Universal Trading for Order Execution with Oracle Policy Distillation. CoRR abs/2103.10860 (2021) - [i33]Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian:
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport. CoRR abs/2106.12950 (2021) - [i32]Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian:
Deep Risk Model: A Deep Learning Solution for Mining Latent Risk Factors to Improve Covariance Matrix Estimation. CoRR abs/2107.05201 (2021) - [i31]Wentao Xu, Weiqing Liu, Jiang Bian, Jian Yin, Tie-Yan Liu:
Instance-wise Graph-based Framework for Multivariate Time Series Forecasting. CoRR abs/2109.06489 (2021) - [i30]Wentao Xu, Weiqing Liu, Lewen Wang, Yingce Xia, Jiang Bian, Jian Yin, Tie-Yan Liu:
HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information. CoRR abs/2110.13716 (2021) - [i29]Zhining Liu, Zhepei Wei, Erxin Yu, Qiang Huang, Kai Guo, Boyang Yu, Zhaonian Cai, Hangting Ye, Wei Cao, Jiang Bian, Pengfei Wei, Jing Jiang, Yi Chang:
IMBENS: Ensemble Class-imbalanced Learning in Python. CoRR abs/2111.12776 (2021) - [i28]Zhining Liu, Pengfei Wei, Zhepei Wei, Boyang Yu, Jing Jiang, Wei Cao, Jiang Bian, Yi Chang:
Towards Inter-class and Intra-class Imbalance in Class-imbalanced Learning. CoRR abs/2111.12791 (2021) - [i27]Wentao Xu, Zhiping Luo, Weiqing Liu, Jiang Bian, Jian Yin, Tie-Yan Liu:
KGE-CL: Contrastive Learning of Knowledge Graph Embeddings. CoRR abs/2112.04871 (2021) - [i26]Wentao Xu, Yingce Xia, Weiqing Liu, Jiang Bian, Jian Yin, Tie-Yan Liu:
SHGNN: Structure-Aware Heterogeneous Graph Neural Network. CoRR abs/2112.06244 (2021) - 2020
- [c44]Zhenhui Xu, Guolin Ke, Jia Zhang, Jiang Bian, Tie-Yan Liu:
Light Multi-Segment Activation for Model Compression. AAAI 2020: 6542-6549 - [c43]Mingqing Xiao
, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu:
Invertible Image Rescaling. ECCV (1) 2020: 126-144 - [c42]Zhining Liu, Wei Cao, Zhifeng Gao, Jiang Bian, Hechang Chen, Yi Chang, Tie-Yan Liu:
Self-paced Ensemble for Highly Imbalanced Massive Data Classification. ICDE 2020: 841-852 - [c41]Xia Hu, Weiqing Liu, Jiang Bian, Jian Pei:
Measuring Model Complexity of Neural Networks with Curve Activation Functions. KDD 2020: 1521-1531 - [c40]Zhining Liu, Pengfei Wei, Jing Jiang, Wei Cao, Jiang Bian, Yi Chang:
MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler. NeurIPS 2020 - [i25]Mingqing Xiao
, Shuxin Zheng
, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu:
Invertible Image Rescaling. CoRR abs/2005.05650 (2020) - [i24]Zhenhui Xu, Linyuan Gong, Guolin Ke, Di He, Shuxin Zheng
, Liwei Wang, Jiang Bian, Tie-Yan Liu:
MC-BERT: Efficient Language Pre-Training via a Meta Controller. CoRR abs/2006.05744 (2020) - [i23]Xia Hu, Weiqing Liu, Jiang Bian, Jian Pei:
Measuring Model Complexity of Neural Networks with Curve Activation Functions. CoRR abs/2006.08962 (2020) - [i22]Yang Fan, Yingce Xia, Lijun Wu, Shufang Xie, Weiqing Liu, Jiang Bian, Tao Qin, Xiang-Yang Li, Tie-Yan Liu:
Learning to Teach with Deep Interactions. CoRR abs/2007.04649 (2020) - [i21]Xueqing Wu, Yingce Xia, Lijun Wu, Shufang Xie, Weiqing Liu, Jiang Bian, Tao Qin, Tie-Yan Liu:
Learn to Use Future Information in Simultaneous Translation. CoRR abs/2007.05290 (2020) - [i20]Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, Tie-Yan Liu:
Qlib: An AI-oriented Quantitative Investment Platform. CoRR abs/2009.11189 (2020) - [i19]Zhining Liu
, Pengfei Wei, Jing Jiang, Wei Cao, Jiang Bian, Yi Chang:
MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler. CoRR abs/2010.08830 (2020) - [i18]Hao Wang, Jia Zhang, Yingce Xia, Jiang Bian, Chao Zhang, Tie-Yan Liu:
COSEA: Convolutional Code Search with Layer-wise Attention. CoRR abs/2010.09520 (2020) - [i17]Hongshun Tang, Lijun Wu, Weiqing Liu, Jiang Bian:
ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting. CoRR abs/2012.06289 (2020) - [i16]Wenlei Shi, Xinran Wei, Jia Zhang, Xiaoyuan Ni, Arthur Jiang, Jiang Bian, Tie-Yan Liu:
Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations. CoRR abs/2012.13099 (2020)
2010 – 2019
- 2019
- [j7]Yijun Wang
, Yingce Xia, Li Zhao, Jiang Bian, Tao Qin
, Enhong Chen
, Tie-Yan Liu:
Semi-Supervised Neural Machine Translation via Marginal Distribution Estimation. IEEE ACM Trans. Audio Speech Lang. Process. 27(10): 1564-1576 (2019) - [c39]Guoqing Liu, Li Zhao, Feidiao Yang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Trust Region Evolution Strategies. AAAI 2019: 4352-4359 - [c38]Zichuan Lin, Li Zhao, Jiang Bian, Tao Qin, Guangwen Yang:
Unified Policy Optimization for Robust Reinforcement Learning. ACML 2019: 395-410 - [c37]Xihan Li, Jia Zhang, Jiang Bian, Yunhai Tong, Tie-Yan Liu:
A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics Network. AAMAS 2019: 980-988 - [c36]Shun Zheng, Wei Cao, Wei Xu, Jiang Bian:
Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction. EMNLP/IJCNLP (1) 2019: 337-346 - [c35]Lewen Wang, Weiqing Liu, Xiao Yang, Jiang Bian:
Conservative or Aggressive? Confidence-Aware Dynamic Portfolio Construction. GlobalSIP 2019: 1-5 - [c34]Xiao Yang, Weiqing Liu, Lewen Wang, Cheng Qu, Jiang Bian:
A Divide-and-Conquer Framework for Attention-based Combination of Multiple Investment Strategies. GlobalSIP 2019: 1-5 - [c33]Guolin Ke, Zhenhui Xu, Jia Zhang, Jiang Bian, Tie-Yan Liu:
DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks. KDD 2019: 384-394 - [c32]Zhige Li, Derek Yang, Li Zhao, Jiang Bian, Tao Qin
, Tie-Yan Liu:
Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding. KDD 2019: 894-902 - [c31]Chi Chen, Li Zhao, Jiang Bian, Chunxiao Xing
, Tie-Yan Liu:
Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction. KDD 2019: 2376-2384 - [c30]Derek Yang, Li Zhao, Zichuan Lin, Tao Qin, Jiang Bian, Tie-Yan Liu:
Fully Parameterized Quantile Function for Distributional Reinforcement Learning. NeurIPS 2019: 6190-6199 - [i15]Xihan Li, Jia Zhang, Jiang Bian, Yunhai Tong, Tie-Yan Liu:
A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics Network. CoRR abs/1903.00714 (2019) - [i14]Shun Zheng, Wei Cao, Wei Xu, Jiang Bian:
Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction. CoRR abs/1904.07535 (2019) - [i13]Zhenhui Xu, Guolin Ke, Jia Zhang, Jiang Bian, Tie-Yan Liu:
Light Multi-segment Activation for Model Compression. CoRR abs/1907.06870 (2019) - [i12]Ziyu Liu, Guolin Ke, Jiang Bian, Tie-Yan Liu:
LightMC: A Dynamic and Efficient Multiclass Decomposition Algorithm. CoRR abs/1908.09362 (2019) - [i11]Zhining Liu
, Wei Cao, Zhifeng Gao, Jiang Bian, Hechang Chen, Yi Chang, Tie-Yan Liu:
Self-paced Ensemble for Highly Imbalanced Massive Data Classification. CoRR abs/1909.03500 (2019) - [i10]Derek Yang, Li Zhao, Zichuan Lin, Tao Qin, Jiang Bian, Tie-Yan Liu:
Fully Parameterized Quantile Function for Distributional Reinforcement Learning. CoRR abs/1911.02140 (2019) - 2018
- [c29]Yijun Wang
, Yingce Xia, Li Zhao, Jiang Bian, Tao Qin, Guiquan Liu, Tie-Yan Liu:
Dual Transfer Learning for Neural Machine Translation with Marginal Distribution Regularization. AAAI 2018: 5553-5560 - [c28]Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu:
Slim-DP: A Multi-Agent System for Communication-Efficient Distributed Deep Learning. AAMAS 2018: 721-729 - [c27]Yi Ding, Weiqing Liu, Jiang Bian, Daoqiang Zhang, Tie-Yan Liu:
Investor-Imitator: A Framework for Trading Knowledge Extraction. KDD 2018: 1310-1319 - [c26]Ziniu Hu, Weiqing Liu, Jiang Bian, Xuanzhe Liu, Tie-Yan Liu:
Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction. WSDM 2018: 261-269 - 2017
- [c25]Yingce Xia, Tao Qin, Wei Chen, Jiang Bian, Nenghai Yu, Tie-Yan Liu:
Dual Supervised Learning. ICML 2017: 3789-3798 - [c24]Yingce Xia, Jiang Bian, Tao Qin
, Nenghai Yu, Tie-Yan Liu:
Dual Inference for Machine Learning. IJCAI 2017: 3112-3118 - [c23]Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu:
Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks. ECML/PKDD (1) 2017: 187-202 - [i9]Yang Fan, Fei Tian, Tao Qin, Jiang Bian, Tie-Yan Liu:
Learning What Data to Learn. CoRR abs/1702.08635 (2017) - [i8]Yingce Xia, Tao Qin, Wei Chen, Jiang Bian, Nenghai Yu, Tie-Yan Liu:
Dual Supervised Learning. CoRR abs/1707.00415 (2017) - [i7]Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu:
Slim-DP: A Light Communication Data Parallelism for DNN. CoRR abs/1709.09393 (2017) - 2016
- [c22]Huazheng Wang, Fei Tian, Bin Gao, Chengjieren Zhu, Jiang Bian, Tie-Yan Liu:
Solving Verbal Questions in IQ Test by Knowledge-Powered Word Embedding. EMNLP 2016: 541-550 - [i6]Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu:
Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks. CoRR abs/1606.00575 (2016) - 2015
- [j6]Bo Long, Jiang Bian, Olivier Chapelle, Ya Zhang, Yoshiyuki Inagaki, Yi Chang:
Active Learning for Ranking through Expected Loss Optimization. IEEE Trans. Knowl. Data Eng. 27(5): 1180-1191 (2015) - [j5]Qing Cui, Bin Gao, Jiang Bian, Siyu Qiu, Hanjun Dai, Tie-Yan Liu:
KNET: A General Framework for Learning Word Embedding Using Morphological Knowledge. ACM Trans. Inf. Syst. 34(1): 4:1-4:25 (2015) - [i5]Huazheng Wang, Bin Gao, Jiang Bian, Fei Tian, Tie-Yan Liu:
Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered Word Embedding. CoRR abs/1505.07909 (2015) - 2014
- [j4]Jiang Bian, Bo Long, Lihong Li, Taesup Moon, Anlei Dong, Yi Chang:
Exploiting User Preference for Online Learning in Web Content Optimization Systems. ACM Trans. Intell. Syst. Technol. 5(2): 33:1-33:23 (2014) - [c21]Yuyu Zhang, Hanjun Dai, Chang Xu, Jun Feng, Taifeng Wang, Jiang Bian, Bin Wang, Tie-Yan Liu:
Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks. AAAI 2014: 1369-1375 - [c20]Chang Xu, Yalong Bai, Jiang Bian, Bin Gao, Gang Wang, Xiaoguang Liu, Tie-Yan Liu:
RC-NET: A General Framework for Incorporating Knowledge into Word Representations. CIKM 2014: 1219-1228 - [c19]Siyu Qiu, Qing Cui, Jiang Bian, Bin Gao, Tie-Yan Liu:
Co-learning of Word Representations and Morpheme Representations. COLING 2014: 141-150 - [c18]Fei Tian, Hanjun Dai, Jiang Bian, Bin Gao, Rui Zhang, Enhong Chen, Tie-Yan Liu:
A Probabilistic Model for Learning Multi-Prototype Word Embeddings. COLING 2014: 151-160 - [c17]Jiang Bian, Bin Gao, Tie-Yan Liu:
Knowledge-Powered Deep Learning for Word Embedding. ECML/PKDD (1) 2014: 132-148 - [c16]Jun Feng, Jiang Bian, Taifeng Wang, Wei Chen, Xiaoyan Zhu, Tie-Yan Liu:
Sampling dilemma: towards effective data sampling for click prediction in sponsored search. WSDM 2014: 103-112 - [i4]Yuyu Zhang, Hanjun Dai, Chang Xu, Jun Feng, Taifeng Wang, Jiang Bian, Bin Wang, Tie-Yan Liu:
Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks. CoRR abs/1404.5772 (2014) - [i3]Bin Gao, Jiang Bian, Tie-Yan Liu:
WordRep: A Benchmark for Research on Learning Word Representations. CoRR abs/1407.1640 (2014) - [i2]Qing Cui, Bin Gao, Jiang Bian, Siyu Qiu, Tie-Yan Liu:
Learning Effective Word Embedding using Morphological Word Similarity. CoRR abs/1407.1687 (2014) - 2013
- [j3]Jiang Bian, Anlei Dong, Xiaofeng He, Srihari Reddy, Yi Chang:
User Action Interpretation for Online Content Optimization. IEEE Trans. Knowl. Data Eng. 25(9): 2161-2174 (2013) - [c15]Taifeng Wang, Jiang Bian, Shusen Liu, Yuyu Zhang, Tie-Yan Liu:
Psychological advertising: exploring user psychology for click prediction in sponsored search. KDD 2013: 563-571 - [c14]Yoshiyuki Inagaki, Jiang Bian, Yi Chang:
An effective general framework for localized content optimization. WWW (Companion Volume) 2013: 65-66 - 2012
- [j2]Jiang Bian, Yi Chang, Yun Fu, Wen-Yen Chen:
Learning to blend vitality rankings from heterogeneous social networks. Neurocomputing 97: 390-397 (2012) - [c13]Bo Long, Jiang Bian, Anlei Dong, Yi Chang:
Enhancing product search by best-selling prediction in e-commerce. CIKM 2012: 2479-2482 - [c12]Xuanhui Wang, Jiang Bian, Yi Chang, Belle L. Tseng:
Model news relatedness through user comments. WWW (Companion Volume) 2012: 629-630 - [i1]Shuang-Hong Yang, Jiang Bian, Hongyuan Zha:
Hybrid Generative/Discriminative Learning for Automatic Image Annotation. CoRR abs/1203.3530 (2012) - 2011
- [c11]Anlei Dong, Jiang Bian, Xiaofeng He, Srihari Reddy, Yi Chang:
User action interpretation for personalized content optimization in recommender systems. CIKM 2011: 2129-2132 - [c10]Jiang Bian, Yi Chang:
A taxonomy of local search: semi-supervised query classification driven by information needs. CIKM 2011: 2425-2428 - [c9]Yoshiyuki Inagaki, Jiang Bian, Yi Chang, Motoko Maki:
Enhancing mobile search using web search log data. SIGIR 2011: 1201-1202 - 2010
- [c8]Shuang-Hong Yang, Jiang Bian, Hongyuan Zha:
Hybrid Generative/Discriminative Learning for Automatic Image Annotation. UAI 2010: 683-690 - [c7]Jiang Bian, Tie-Yan Liu, Tao Qin, Hongyuan Zha:
Ranking with query-dependent loss for web search. WSDM 2010: 141-150 - [c6]Jiang Bian, Xin Li, Fan Li, Zhaohui Zheng, Hongyuan Zha:
Ranking specialization for web search: a divide-and-conquer approach by using topical RankSVM. WWW 2010: 131-140
2000 – 2009
- 2009
- [j1]Eugene Agichtein, Yandong Liu, Jiang Bian:
Modeling information-seeker satisfaction in community question answering. ACM Trans. Knowl. Discov. Data 3(2): 10:1-10:27 (2009) - [c5]Jiang Bian, Yandong Liu, Ding Zhou, Eugene Agichtein, Hongyuan Zha:
Learning to recognize reliable users and content in social media with coupled mutual reinforcement. WWW 2009: 51-60 - 2008
- [c4]Jiang Bian, Yandong Liu, Eugene Agichtein, Hongyuan Zha:
A few bad votes too many?: towards robust ranking in social media. AIRWeb 2008: 53-60 - [c3]Yandong Liu, Jiang Bian, Eugene Agichtein:
Predicting information seeker satisfaction in community question answering. SIGIR 2008: 483-490 - [c2]Jiang Bian, Yandong Liu, Eugene Agichtein, Hongyuan Zha:
Finding the right facts in the crowd: factoid question answering over social media. WWW 2008: 467-476 - [c1]Ding Zhou, Jiang Bian, Shuyi Zheng, Hongyuan Zha, C. Lee Giles
:
Exploring social annotations for information retrieval. WWW 2008: 715-724
Coauthor Index

manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
load content from web.archive.org
Privacy notice: By enabling the option above, your browser will contact the API of web.archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
Tweets on dblp homepage
Show tweets from on the dblp homepage.
Privacy notice: By enabling the option above, your browser will contact twitter.com and twimg.com to load tweets curated by our Twitter account. At the same time, Twitter will persistently store several cookies with your web browser. While we did signal Twitter to not track our users by setting the "dnt" flag, we do not have any control over how Twitter uses your data. So please proceed with care and consider checking the Twitter privacy policy.
last updated on 2022-06-28 22:07 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint