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ORCIDJiang 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
![[0000-0002-2238-5429]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-2238-5429")
— 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
- Jiang Bian 0006 — University of Technology Sydney, Australia
- Jiang Bian 0007 — University of Hong Kong, Pokfulam, Hong Kong
- Jiang Bian 0008 — Shanghai Jiaotong University, Department of Computer Science and Engineering, China
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2020 – today
- 2023
[c80]Yan Jin, Yuandong Ding, Xuanhao Pan, Kun He, Li Zhao, Tao Qin, Lei Song, Jiang Bian:
Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problem. AAAI 2023: 8132-8140- [c79]Xuanhao Pan, Yan Jin, Yuandong Ding, Mingxiao Feng, Li Zhao, Lei Song, Jiang Bian:
H-TSP: Hierarchically Solving the Large-Scale Traveling Salesman Problem. AAAI 2023: 9345-9353 - [c78]Yihan Wu, Junliang Guo, Xu Tan, Chen Zhang, Bohan Li, Ruihua Song, Lei He, Sheng Zhao, Arul Menezes, Jiang Bian:
VideoDubber: Machine Translation with Speech-Aware Length Control for Video Dubbing. AAAI 2023: 13772-13779 - [c77]Di He, Shanda Li, Wenlei Shi, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu:
Learning Physics-Informed Neural Networks without Stacked Back-propagation. AISTATS 2023: 3034-3047 - [c76]Yuanying Cai, Chuheng Zhang, Hanye Zhao, Li Zhao, Jiang Bian:
Curriculum Offline Reinforcement Learning. AAMAS 2023: 1221-1229 - [c75]Hangting Ye, Zhining Liu, Xinyi Shen, Wei Cao, Shun Zheng, Xiaofan Gui, Huishuai Zhang, Yi Chang, Jiang Bian:
UADB: Unsupervised Anomaly Detection Booster. ICDE 2023: 2593-2606 - [c74]Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian:
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping. ICLR 2023 - [c73]Jinpeng Zhang, Yufeng Zheng, Chuheng Zhang, Li Zhao, Lei Song, Yuan Zhou, Jiang Bian:
Robust Situational Reinforcement Learning in Face of Context Disturbances. ICML 2023: 41973-41989 - [c72]Hangting Ye, Zhining Liu, Wei Cao, Amir M. Amiri, Jiang Bian, Yi Chang, Jon D. Lurie, Jim Weinstein, Tie-Yan Liu:
Web-based Long-term Spine Treatment Outcome Forecasting. KDD 2023: 3082-3092 - [c71]Jiawen Zhang, Shun Zheng, Wei Cao, Jiang Bian, Jia Li:
Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series. KDD 2023: 3273-3285 - [c70]Yuchen Fang, Zhenggang Tang, Kan Ren, Weiqing Liu, Li Zhao, Jiang Bian, Dongsheng Li, Weinan Zhang, Yong Yu, Tie-Yan Liu:
Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance. KDD 2023: 4003-4012 - [c69]Lewen Wang, Haozhe Zhao, Cunguang Feng, Weiqing Liu, Congrui Huang, Marco Santoni, Manuel Cristofaro, Paola Jafrancesco, Jiang Bian:
Removing Camouflage and Revealing Collusion: Leveraging Gang-crime Pattern in Fraudster Detection. KDD 2023: 5104-5115 - [i77]Xu Tan, Tao Qin, Jiang Bian, Tie-Yan Liu, Yoshua Bengio:
Regeneration Learning: A Learning Paradigm for Data Generation. CoRR abs/2301.08846 (2023) - [i76]Kai Shen, Junliang Guo, Xu Tan, Siliang Tang, Rui Wang, Jiang Bian:
A Study on ReLU and Softmax in Transformer. CoRR abs/2302.06461 (2023) - [i75]Zenghao Chai, Tianke Zhang, Tianyu He, Xu Tan, Tadas Baltrusaitis, HsiangTao Wu, Runnan Li, Sheng Zhao, Chun Yuan, Jiang Bian:
HiFace: High-Fidelity 3D Face Reconstruction by Learning Static and Dynamic Details. CoRR abs/2303.11225 (2023) - [i74]Chenpeng Du, Qi Chen, Tianyu He, Xu Tan, Xie Chen, Kai Yu, Sheng Zhao, Jiang Bian:
DAE-Talker: High Fidelity Speech-Driven Talking Face Generation with Diffusion Autoencoder. CoRR abs/2303.17550 (2023) - [i73]Yuancheng Wang, Zeqian Ju, Xu Tan, Lei He, Zhizheng Wu, Jiang Bian, Sheng Zhao:
AUDIT: Audio Editing by Following Instructions with Latent Diffusion Models. CoRR abs/2304.00830 (2023) - [i72]Kai Shen, Zeqian Ju, Xu Tan, Yanqing Liu, Yichong Leng, Lei He, Tao Qin, Sheng Zhao, Jiang Bian:
NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers. CoRR abs/2304.09116 (2023) - [i71]Xuanhao Pan, Yan Jin, Yuandong Ding, Mingxiao Feng, Li Zhao, Lei Song, Jiang Bian:
H-TSP: Hierarchically Solving the Large-Scale Travelling Salesman Problem. CoRR abs/2304.09395 (2023) - [i70]Yan Jin, Yuandong Ding, Xuanhao Pan, Kun He, Li Zhao, Tao Qin, Lei Song, Jiang Bian:
Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problem. CoRR abs/2304.09407 (2023) - [i69]Shufang Xie, Huishuai Zhang, Junliang Guo, Xu Tan, Jiang Bian, Hany Hassan Awadalla, Arul Menezes, Tao Qin, Rui Yan:
ResiDual: Transformer with Dual Residual Connections. CoRR abs/2304.14802 (2023) - [i68]Ang Lv, Xu Tan, Peiling Lu, Wei Ye, Shikun Zhang, Jiang Bian, Rui Yan:
GETMusic: Generating Any Music Tracks with a Unified Representation and Diffusion Framework. CoRR abs/2305.10841 (2023) - [i67]Bei Li, Rui Wang, Junliang Guo, Kaitao Song, Xu Tan, Hany Hassan, Arul Menezes, Tong Xiao, Jiang Bian, JingBo Zhu:
Deliberate then Generate: Enhanced Prompting Framework for Text Generation. CoRR abs/2305.19835 (2023) - [i66]Peiling Lu, Xin Xu, Chenfei Kang, Botao Yu, Chengyi Xing, Xu Tan, Jiang Bian:
MuseCoco: Generating Symbolic Music from Text. CoRR abs/2306.00110 (2023) - [i65]Hangting Ye, Zhining Liu, Xinyi Shen, Wei Cao, Shun Zheng, Xiaofan Gui, Huishuai Zhang, Yi Chang, Jiang Bian:
UADB: Unsupervised Anomaly Detection Booster. CoRR abs/2306.01997 (2023) - [i64]Linjie Xu, Zhengyao Jiang, Jinyu Wang, Lei Song, Jiang Bian:
Mildly Constrained Evaluation Policy for Offline Reinforcement Learning. CoRR abs/2306.03680 (2023) - [i63]Xianliang Yang, Zhihao Liu, Wei Jiang, Chuheng Zhang, Li Zhao, Lei Song, Jiang Bian:
A Versatile Multi-Agent Reinforcement Learning Benchmark for Inventory Management. CoRR abs/2306.07542 (2023) - [i62]Jiawen Zhang, Shun Zheng, Wei Cao, Jiang Bian, Jia Li:
Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series. CoRR abs/2306.09368 (2023) - [i61]Chenfei Kang, Peiling Lu, Botao Yu, Xu Tan, Wei Ye, Shikun Zhang, Jiang Bian:
EmoGen: Eliminating Subjective Bias in Emotional Music Generation. CoRR abs/2307.01229 (2023) - [i60]Yuchen Fang, Zhenggang Tang, Kan Ren, Weiqing Liu, Li Zhao, Jiang Bian, Dongsheng Li, Weinan Zhang, Yong Yu, Tie-Yan Liu:
Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance. CoRR abs/2307.03119 (2023) - [i59]Tianlang He, Keyan Lu, Chang Xu, Yang Liu, Weiqing Liu, S.-H. Gary Chan, Jiang Bian:
Efficient Behavior-consistent Calibration for Multi-agent Market Simulation. CoRR abs/2307.12987 (2023) - [i58]Lei Song, Chuheng Zhang, Li Zhao, Jiang Bian:
Pre-Trained Large Language Models for Industrial Control. CoRR abs/2308.03028 (2023) - [i57]Xianfeng Jiao, Zizhong Li, Chang Xu, Yang Liu, Weiqing Liu, Jiang Bian:
Microstructure-Empowered Stock Factor Extraction and Utilization. CoRR abs/2308.08135 (2023) - [i56]Yichong Leng, Zhifang Guo, Kai Shen, Xu Tan, Zeqian Ju, Yanqing Liu, Yufei Liu, Dongchao Yang, Leying Zhang, Kaitao Song, Lei He, Xiang-Yang Li, Sheng Zhao, Tao Qin, Jiang Bian:
PromptTTS 2: Describing and Generating Voices with Text Prompt. CoRR abs/2309.02285 (2023) - [i55]Qingyan Guo, Rui Wang, Junliang Guo, Bei Li, Kaitao Song, Xu Tan, Guoqing Liu, Jiang Bian, Yujiu Yang:
Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers. CoRR abs/2309.08532 (2023) - 2022
- [c68]Wendi Li, Xiao Yang, Weiqing Liu, Yingce Xia, Jiang Bian:
DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation. AAAI 2022: 4092-4100 - [c67]Yuting Xing, Hangting Ye, Xiaoyu Zhang, Wei Cao, Shun Zheng, Jiang Bian, Yike Guo:
A continuous glucose monitoring measurements forecasting approach via sporadic blood glucose monitoring. BIBM 2022: 860-863 - [c66]Swati Sharma, Srinivasan Iyengar, Shun Zheng, Kshitij Kapoor, Wei Cao, Jiang Bian, Shivkumar Kalyanaraman, John Lemmon:
A Graph-based Spatiotemporal Model for Energy Markets. CIKM 2022: 4459-4463 - [c65]Zhiping Luo, Wentao Xu, Weiqing Liu, Jiang Bian, Jian Yin, Tie-Yan Liu:
KGE-CL: Contrastive Learning of Tensor Decomposition Based Knowledge Graph Embeddings. COLING 2022: 2598-2607 - [c64]Yuanying Cai, Chuheng Zhang, Li Zhao, Wei Shen, Xuyun Zhang, Lei Song, Jiang Bian, Tao Qin, Tieyan Liu:
TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets. ICDM 2022: 21-30 - [c63]Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu:
DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting. ICLR 2022 - [c62]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. IJCAI 2022: 3659-3665 - [c61]Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian:
Learning Differential Operators for Interpretable Time Series Modeling. KDD 2022: 1192-1201 - [c60]Xiaozhuang Song, Shun Zheng, Wei Cao, James J. Q. Yu, Jiang Bian:
Efficient and Effective Multi-task Grouping via Meta Learning on Task Combinations. NeurIPS 2022 - [c59]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 - [i54]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) - [i53]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) - [i52]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) - [i51]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) - [i50]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) - [i49]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) - [i48]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) - [i47]Tianping Zhang, Yizhuo Zhang, Wei Cao, Jiang Bian, Xiaohan Yi, Shun Zheng, Jian Li:
Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures. CoRR abs/2207.01186 (2022) - [i46]Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian:
Learning Differential Operators for Interpretable Time Series Modeling. CoRR abs/2209.01491 (2022) - [i45]Yukun Zheng, Jiang Bian, Guanghao Meng, Chao Zhang, Honggang Wang, Zhixuan Zhang, Sen Li, Tao Zhuang, Qingwen Liu, Xiaoyi Zeng:
Multi-Objective Personalized Product Retrieval in Taobao Search. CoRR abs/2210.04170 (2022) - [i44]Yihan Wu, Junliang Guo, Xu Tan, Chen Zhang, Bohan Li, Ruihua Song, Lei He, Sheng Zhao, Arul Menezes, Jiang Bian:
VideoDubber: Machine Translation with Speech-Aware Length Control for Video Dubbing. CoRR abs/2211.16934 (2022) - [i43]Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian:
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping. CoRR abs/2212.01539 (2022) - [i42]Yuanying Cai, Chuheng Zhang, Li Zhao, Wei Shen, Xuyun Zhang, Lei Song, Jiang Bian, Tao Qin, Tieyan Liu:
TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets. CoRR abs/2212.02125 (2022) - [i41]Anni Tang, Tianyu He, Xu Tan, Jun Ling, Runnan Li, Sheng Zhao, Li Song, Jiang Bian:
Memories are One-to-Many Mapping Alleviators in Talking Face Generation. CoRR abs/2212.05005 (2022) - [i40]Yuandong Ding, Mingxiao Feng, Guozi Liu, Wei Jiang, Chuheng Zhang, Li Zhao, Lei Song, Houqiang Li, Yan Jin, Jiang Bian:
Multi-Agent Reinforcement Learning with Shared Resources for Inventory Management. CoRR abs/2212.07684 (2022) - [i39]Zhujin Gao, Junliang Guo, Xu Tan, Yongxin Zhu, Fang Zhang, Jiang Bian, Linli Xu:
Difformer: Empowering Diffusion Model on Embedding Space for Text Generation. CoRR abs/2212.09412 (2022) - [i38]Zehua Chen, Yihan Wu, Yichong Leng, Jiawei Chen, Haohe Liu, Xu Tan, Yang Cui, Ke Wang, Lei He, Sheng Zhao, Jiang Bian, Danilo P. Mandic:
ResGrad: Residual Denoising Diffusion Probabilistic Models for Text to Speech. CoRR abs/2212.14518 (2022) - 2021
- [j11]Guoqing Liu, Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Demonstration actor critic. Neurocomputing 434: 194-202 (2021) - [j10]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) - [j9]Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Guolin Ke, Jingwu Chen, Jiang Bian, Hui Xiong, Qing He:
Deep Subdomain Adaptation Network for Image Classification. IEEE Trans. Neural Networks Learn. Syst. 32(4): 1713-1722 (2021) - [c58]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 - [c57]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 - [c56]Shun Zheng, Wei Cao, Wei Xu, Jiang Bian:
Revisiting the Evaluation of End-to-end Event Extraction. ACL/IJCNLP (Findings) 2021: 4609-4617 - [c55]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 - [c54]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 - [c53]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 - [c52]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 - [c51]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 - [c50]Pushi Zhang, Li Zhao, Guoqing Liu, Jiang Bian, Minlie Huang, Tao Qin, Tie-Yan Liu:
Independence-aware Advantage Estimation. IJCAI 2021: 3349-3355 - [c49]Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian:
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport. KDD 2021: 1017-1026 - [c48]Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu:
REST: Relational Event-driven Stock Trend Forecasting. WWW 2021: 1-10 - [i37]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) - [i36]Xia Hu, Lingyang Chu, Jian Pei, Weiqing Liu, Jiang Bian:
Model Complexity of Deep Learning: A Survey. CoRR abs/2103.05127 (2021) - [i35]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) - [i34]Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Guolin Ke, Jingwu Chen, Jiang Bian, Hui Xiong, Qing He:
Deep Subdomain Adaptation Network for Image Classification. CoRR abs/2106.09388 (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
- [c47]Zhenhui Xu, Guolin Ke, Jia Zhang, Jiang Bian, Tie-Yan Liu:
Light Multi-Segment Activation for Model Compression. AAAI 2020: 6542-6549 - [c46]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 - [c45]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 - [c44]Xia Hu, Weiqing Liu, Jiang Bian, Jian Pei:
Measuring Model Complexity of Neural Networks with Curve Activation Functions. KDD 2020: 1521-1531 - [c43]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
- [j8]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) - [c42]Guoqing Liu, Li Zhao, Feidiao Yang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Trust Region Evolution Strategies. AAAI 2019: 4352-4359 - [c41]Zichuan Lin, Li Zhao, Jiang Bian, Tao Qin, Guangwen Yang:
Unified Policy Optimization for Robust Reinforcement Learning. ACML 2019: 395-410 - [c40]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 - [c39]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 - [c38]Lewen Wang, Weiqing Liu, Xiao Yang, Jiang Bian:
Conservative or Aggressive? Confidence-Aware Dynamic Portfolio Construction. GlobalSIP 2019: 1-5 - [c37]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 - [c36]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 - [c35]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 - [c34]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 - [c33]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<