BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning
Xiao Yang, Xu Yang, Weiqing Liu, Lewen Wang, Jiang Bian
2024 Neural Information Processing Systems | October 2024
Weiqing Liu
Directeur principal de la recherche
Papiers de Collaboration
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MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
Junjie Li, Yang Liu, Weiqing Liu, Shikai Fang, Lewen Wang, Chang Xu, Jiang Bian
September 2024
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Controllable Financial Market Generation with Diffusion Guided Meta Agent
Yu-Hao Huang, Chang Xu, Yang Liu, Weiqing Liu, Wu-Jun Li, Jiang Bian
August 2024
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RD2Bench: Toward Data-Centric Automatic R&D
Haotian Chen, Xinjie Shen, Zeqi Ye, Xiao Yang, Xu Yang, Weiqing Liu, Jiang Bian
April 2024
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MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process
Xinyao Fan, Yueying Wu, Chang Xu, Yuhao Huang, Weiqing Liu, Jiang Bian
ICLR 2024 | March 2024
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Leveraging Large Language Model for Automatic Evolving of Industrial Data-Centric R&D Cycle
Xu Yang, Xiao Yang, Weiqing Liu, Jinhui Li, Peng Yu, Zeqi Ye, Jiang Bian
October 2023
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Learning Differential Operators for Interpretable Time Series Modeling
Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian
KDD 2022 | August 2022
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Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble
Zhengyu Yang, Kan Ren, Xufang Luo, Minghuan Liu, Weiqing Liu, Jiang Bian, Weinan Zhang, Dongsheng Li
IJCAI 2022 | July 2022
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Multi-Granularity Residual Learning with Confidence Estimation for Time Series Prediction
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
WWW 2022 | April 2022
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DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation
Wendi Li, Xiao Yang, Weiqing Liu, Yingce Xia, Jiang Bian
AAAI 2022 | January 2022
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ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting
Hongshun Tang, Lijun Wu, Weiqing Liu, Jiang Bian
December 2021
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Deep Risk Model: A Deep Learning Solution for Mining Latent Risk Factors to Improve Covariance Matrix Estimation
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
ICAIF 2021 | November 2021
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Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
KDD 2021 | August 2021
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Temporally Correlated Task Scheduling for Sequence Learning
Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie, Tao Qin, Tie-Yan Liu
2021 International Conference on Machine Learning | July 2021
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REST: Relational Event-driven Stock Trend Forecasting
Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu
2021 The Web Conference | April 2021
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Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
CIKM 221 | April 2021
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Universal Trading for Order Execution with Oracle Policy Distillation
Yuchen Fang, Kan Ren, Weiqing Liu, Dong Zhou, Weinan Zhang, Jiang Bian, Yong Yu, Tie-Yan Liu
AAAI | February 2021
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Qlib: An AI-oriented Quantitative Investment Platform.
Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, Tie-Yan Liu
September 2020
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A Divide-and-Conquer Framework for Attention-based Combination of Multiple Investment Strategies
Xiao Yang, Weiqing Liu, Lewen Wang, Cheng Qu, Jiang Bian
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019
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Conservative or Aggressive? Confidence-Aware Dynamic Portfolio Construction
Lewen Wang, Weiqing Liu, Xiao Yang, Jiang Bian
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019
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Investor-Imitator: A Framework for Trading Knowledge Extraction
Yi Ding, Weiqing Liu, Jiang Bian, Daoqiang Zhang, Tie-Yan Liu
Knowledge Discovery & Data Mining | July 2018
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BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning
Xiao Yang, Xu Yang, Weiqing Liu, Lewen Wang, Jiang Bian
2024 Neural Information Processing Systems | October 2024
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MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
Junjie Li, Yang Liu, Weiqing Liu, Shikai Fang, Lewen Wang, Chang Xu, Jiang Bian
September 2024
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Controllable Financial Market Generation with Diffusion Guided Meta Agent
Yu-Hao Huang, Chang Xu, Yang Liu, Weiqing Liu, Wu-Jun Li, Jiang Bian
August 2024
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RD2Bench: Toward Data-Centric Automatic R&D
Haotian Chen, Xinjie Shen, Zeqi Ye, Xiao Yang, Xu Yang, Weiqing Liu, Jiang Bian
April 2024
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MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process
Xinyao Fan, Yueying Wu, Chang Xu, Yuhao Huang, Weiqing Liu, Jiang Bian
ICLR 2024 | March 2024
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Leveraging Large Language Model for Automatic Evolving of Industrial Data-Centric R&D Cycle
Xu Yang, Xiao Yang, Weiqing Liu, Jinhui Li, Peng Yu, Zeqi Ye, Jiang Bian
October 2023
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Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble
Zhengyu Yang, Kan Ren, Xufang Luo, Minghuan Liu, Weiqing Liu, Jiang Bian, Weinan Zhang, Dongsheng Li
IJCAI 2022 | July 2022
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DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation
Wendi Li, Xiao Yang, Weiqing Liu, Yingce Xia, Jiang Bian
AAAI 2022 | January 2022
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ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting
Hongshun Tang, Lijun Wu, Weiqing Liu, Jiang Bian
December 2021
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Deep Risk Model: A Deep Learning Solution for Mining Latent Risk Factors to Improve Covariance Matrix Estimation
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
ICAIF 2021 | November 2021
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Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
KDD 2021 | August 2021
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Temporally Correlated Task Scheduling for Sequence Learning
Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie, Tao Qin, Tie-Yan Liu
2021 International Conference on Machine Learning | July 2021
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Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
CIKM 221 | April 2021
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REST: Relational Event-driven Stock Trend Forecasting
Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu
2021 The Web Conference | April 2021
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Universal Trading for Order Execution with Oracle Policy Distillation
Yuchen Fang, Kan Ren, Weiqing Liu, Dong Zhou, Weinan Zhang, Jiang Bian, Yong Yu, Tie-Yan Liu
AAAI | February 2021
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Qlib: An AI-oriented Quantitative Investment Platform.
Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, Tie-Yan Liu
September 2020
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Conservative or Aggressive? Confidence-Aware Dynamic Portfolio Construction
Lewen Wang, Weiqing Liu, Xiao Yang, Jiang Bian
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019
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A Divide-and-Conquer Framework for Attention-based Combination of Multiple Investment Strategies
Xiao Yang, Weiqing Liu, Lewen Wang, Cheng Qu, Jiang Bian
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019
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Investor-Imitator: A Framework for Trading Knowledge Extraction
Yi Ding, Weiqing Liu, Jiang Bian, Daoqiang Zhang, Tie-Yan Liu
Knowledge Discovery & Data Mining | July 2018
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MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
Junjie Li, Yang Liu, Weiqing Liu, Shikai Fang, Lewen Wang, Chang Xu, Jiang Bian
September 2024
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Controllable Financial Market Generation with Diffusion Guided Meta Agent
Yu-Hao Huang, Chang Xu, Yang Liu, Weiqing Liu, Wu-Jun Li, Jiang Bian
August 2024
-
RD2Bench: Toward Data-Centric Automatic R&D
Haotian Chen, Xinjie Shen, Zeqi Ye, Xiao Yang, Xu Yang, Weiqing Liu, Jiang Bian
April 2024
-
Leveraging Large Language Model for Automatic Evolving of Industrial Data-Centric R&D Cycle
Xu Yang, Xiao Yang, Weiqing Liu, Jinhui Li, Peng Yu, Zeqi Ye, Jiang Bian
October 2023
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Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
CIKM 221 | April 2021
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Learning Differential Operators for Interpretable Time Series Modeling
Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian
KDD 2022 | August 2022
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Multi-Granularity Residual Learning with Confidence Estimation for Time Series Prediction
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
WWW 2022 | April 2022
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MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
Junjie Li, Yang Liu, Weiqing Liu, Shikai Fang, Lewen Wang, Chang Xu, Jiang Bian
September 2024
-
Controllable Financial Market Generation with Diffusion Guided Meta Agent
Yu-Hao Huang, Chang Xu, Yang Liu, Weiqing Liu, Wu-Jun Li, Jiang Bian
August 2024
-
RD2Bench: Toward Data-Centric Automatic R&D
Haotian Chen, Xinjie Shen, Zeqi Ye, Xiao Yang, Xu Yang, Weiqing Liu, Jiang Bian
April 2024
-
Leveraging Large Language Model for Automatic Evolving of Industrial Data-Centric R&D Cycle
Xu Yang, Xiao Yang, Weiqing Liu, Jinhui Li, Peng Yu, Zeqi Ye, Jiang Bian
October 2023
-
ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting
Hongshun Tang, Lijun Wu, Weiqing Liu, Jiang Bian
December 2021
-
Qlib: An AI-oriented Quantitative Investment Platform.
Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, Tie-Yan Liu
September 2020
-
-
-
BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning
Xiao Yang, Xu Yang, Weiqing Liu, Lewen Wang, Jiang Bian
2024 Neural Information Processing Systems | October 2024
-
MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process
Xinyao Fan, Yueying Wu, Chang Xu, Yuhao Huang, Weiqing Liu, Jiang Bian
ICLR 2024 | March 2024
-
Learning Differential Operators for Interpretable Time Series Modeling
Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian
KDD 2022 | August 2022
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Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble
Zhengyu Yang, Kan Ren, Xufang Luo, Minghuan Liu, Weiqing Liu, Jiang Bian, Weinan Zhang, Dongsheng Li
IJCAI 2022 | July 2022
-
Multi-Granularity Residual Learning with Confidence Estimation for Time Series Prediction
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
WWW 2022 | April 2022
-
DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation
Wendi Li, Xiao Yang, Weiqing Liu, Yingce Xia, Jiang Bian
AAAI 2022 | January 2022
-
Deep Risk Model: A Deep Learning Solution for Mining Latent Risk Factors to Improve Covariance Matrix Estimation
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
ICAIF 2021 | November 2021
-
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
KDD 2021 | August 2021
-
Temporally Correlated Task Scheduling for Sequence Learning
Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie, Tao Qin, Tie-Yan Liu
2021 International Conference on Machine Learning | July 2021
-
Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
CIKM 221 | April 2021
-
REST: Relational Event-driven Stock Trend Forecasting
Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu
2021 The Web Conference | April 2021
-
Universal Trading for Order Execution with Oracle Policy Distillation
Yuchen Fang, Kan Ren, Weiqing Liu, Dong Zhou, Weinan Zhang, Jiang Bian, Yong Yu, Tie-Yan Liu
AAAI | February 2021
-
Conservative or Aggressive? Confidence-Aware Dynamic Portfolio Construction
Lewen Wang, Weiqing Liu, Xiao Yang, Jiang Bian
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019
-
A Divide-and-Conquer Framework for Attention-based Combination of Multiple Investment Strategies
Xiao Yang, Weiqing Liu, Lewen Wang, Cheng Qu, Jiang Bian
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019
-
Investor-Imitator: A Framework for Trading Knowledge Extraction
Yi Ding, Weiqing Liu, Jiang Bian, Daoqiang Zhang, Tie-Yan Liu
Knowledge Discovery & Data Mining | July 2018
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