Liu, Tie-Yan

165 publications

NeurIPS 2024 Bridging Geometric States via Geometric Diffusion Bridge Shengjie Luo, Yixian Xu, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang

ICML 2024 GeoMFormer: A General Architecture for Geometric Molecular Representation Learning Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang

ICLR 2024 Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation Yunyang Li, Yusong Wang, Lin Huang, Han Yang, Xinran Wei, Jia Zhang, Tong Wang, Zun Wang, Bin Shao, Tie-Yan Liu

NeurIPS 2024 Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning Yuxuan Ren, Dihan Zheng, Chang Liu, Peiran Jin, Yu Shi, Lin Huang, Jiyan He, Shengjie Luo, Tao Qin, Tie-Yan Liu

IJCAI 2024 Re-Creation of Creations: A New Paradigm for Lyric-to-Melody Generation Ang Lv, Xu Tan, Tao Qin, Tie-Yan Liu, Rui Yan

AAAI 2024 Regeneration Learning: A Learning Paradigm for Data Generation Xu Tan, Tao Qin, Jiang Bian, Tie-Yan Liu, Yoshua Bengio

ICML 2024 Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction He Zhang, Chang Liu, Zun Wang, Xinran Wei, Siyuan Liu, Nanning Zheng, Bin Shao, Tie-Yan Liu

ICLR 2023 $\mathcal{O}$-GNN: Incorporating Ring Priors into Molecular Modeling Jinhua Zhu, Kehan Wu, Bohan Wang, Yingce Xia, Shufang Xie, Qi Meng, Lijun Wu, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu

AAAI 2023 AMOM: Adaptive Masking over Masking for Conditional Masked Language Model Yisheng Xiao, Ruiyang Xu, Lijun Wu, Juntao Li, Tao Qin, Tie-Yan Liu, Min Zhang

ICLR 2023 De Novo Molecular Generation via Connection-Aware Motif Mining Zijie Geng, Shufang Xie, Yingce Xia, Lijun Wu, Tao Qin, Jie Wang, Yongdong Zhang, Feng Wu, Tie-Yan Liu

AAAI 2023 Deep Latent Regularity Network for Modeling Stochastic Partial Differential Equations Shiqi Gong, Peiyan Hu, Qi Meng, Yue Wang, Rongchan Zhu, Bingguang Chen, Zhiming Ma, Hao Ni, Tie-Yan Liu

NeurIPS 2023 FABind: Fast and Accurate Protein-Ligand Binding Qizhi Pei, Kaiyuan Gao, Lijun Wu, Jinhua Zhu, Yingce Xia, Shufang Xie, Tao Qin, Kun He, Tie-Yan Liu, Rui Yan

NeurIPSW 2023 GeoMFormer: A General Architecture for Geometric Molecular Representation Learning Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang

NeurIPS 2023 Geometric Transformer with Interatomic Positional Encoding Yusong Wang, Shaoning Li, Tong Wang, Bin Shao, Nanning Zheng, Tie-Yan Liu

TMLR 2023 Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent Da Yu, Gautam Kamath, Janardhan Kulkarni, Tie-Yan Liu, Jian Yin, Huishuai Zhang

AISTATS 2023 Learning Physics-Informed Neural Networks Without Stacked Back-Propagation Di He, Shanda Li, Wenlei Shi, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu

ICLR 2023 Making Better Decision by Directly Planning in Continuous Control Jinhua Zhu, Yue Wang, Lijun Wu, Tao Qin, Wengang Zhou, Tie-Yan Liu, Houqiang Li

ICML 2023 NeuralStagger: Accelerating Physics-Constrained Neural PDE Solver with Spatial-Temporal Decomposition Xinquan Huang, Wenlei Shi, Qi Meng, Yue Wang, Xiaotian Gao, Jia Zhang, Tie-Yan Liu

ICLR 2023 One Transformer Can Understand Both 2D & 3D Molecular Data Shengjie Luo, Tianlang Chen, Yixian Xu, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He

ICML 2023 Retrosynthetic Planning with Dual Value Networks Guoqing Liu, Di Xue, Shufang Xie, Yingce Xia, Austin Tripp, Krzysztof Maziarz, Marwin Segler, Tao Qin, Zongzhang Zhang, Tie-Yan Liu

AAAI 2023 SoftCorrect: Error Correction with Soft Detection for Automatic Speech Recognition Yichong Leng, Xu Tan, Wenjie Liu, Kaitao Song, Rui Wang, Xiang-Yang Li, Tao Qin, Edward Lin, Tie-Yan Liu

NeurIPS 2022 An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context Xiaoyu Chen, Xiangming Zhu, Yufeng Zheng, Pushi Zhang, Li Zhao, Wenxue Cheng, Peng Cheng, Yongqiang Xiong, Tao Qin, Jianyu Chen, Tie-Yan Liu

ICML 2022 Analyzing and Mitigating Interference in Neural Architecture Search Jin Xu, Xu Tan, Kaitao Song, Renqian Luo, Yichong Leng, Tao Qin, Tie-Yan Liu, Jian Li

NeurIPS 2022 BinauralGrad: A Two-Stage Conditional Diffusion Probabilistic Model for Binaural Audio Synthesis Yichong Leng, Zehua Chen, Junliang Guo, Haohe Liu, Jiawei Chen, Xu Tan, Danilo P. Mandic, Lei He, Xiangyang Li, Tao Qin, Sheng Zhao, Tie-Yan Liu

ICLR 2022 DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu

TMLR 2022 Direct Molecular Conformation Generation Jinhua Zhu, Yingce Xia, Chang Liu, Lijun Wu, Shufang Xie, Yusong Wang, Tong Wang, Tao Qin, Wengang Zhou, Houqiang Li, Haiguang Liu, Tie-Yan Liu

NeurIPS 2022 Does Momentum Change the Implicit Regularization on Separable Data? Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

ICLR 2022 Gradient Information Matters in Policy Optimization by Back-Propagating Through Model Chongchong Li, Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu

NeurIPS 2022 Museformer: Transformer with Fine- and Coarse-Grained Attention for Music Generation Botao Yu, Peiling Lu, Rui Wang, Wei Hu, Xu Tan, Wei Ye, Shikun Zhang, Tao Qin, Tie-Yan Liu

ICLR 2022 PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu

NeurIPS 2022 Quantized Training of Gradient Boosting Decision Trees Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu

ICML 2022 SE(3) Equivariant Graph Neural Networks with Complete Local Frames Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Nanning Zheng, Bin Shao, Tie-Yan Liu

MLJ 2022 Stabilize Deep ResNet with a Sharp Scaling Factor Τ Huishuai Zhang, Da Yu, Mingyang Yi, Wei Chen, Tie-Yan Liu

ICML 2022 Supervised Off-Policy Ranking Yue Jin, Yue Zhang, Tao Qin, Xudong Zhang, Jian Yuan, Houqiang Li, Tie-Yan Liu

ICLR 2022 Target-Side Input Augmentation for Sequence to Sequence Generation Shufang Xie, Ang Lv, Yingce Xia, Lijun Wu, Tao Qin, Tie-Yan Liu, Rui Yan

NeurIPS 2022 Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu

ICLR 2022 Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality Jiawei Huang, Jinglin Chen, Li Zhao, Tao Qin, Nan Jiang, Tie-Yan Liu

CVPR 2022 Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu

NeurIPS 2022 Your Transformer May Not Be as Powerful as You Expect Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He

IJCAI 2021 A Survey on Low-Resource Neural Machine Translation Rui Wang, Xu Tan, Renqian Luo, Tao Qin, Tie-Yan Liu

ICLR 2021 AdaSpeech: Adaptive Text to Speech for Custom Voice Mingjian Chen, Xu Tan, Bohan Li, Yanqing Liu, Tao Qin, Sheng Zhao, Tie-Yan Liu

NeurIPS 2021 Co-Evolution Transformer for Protein Contact Prediction He Zhang, Fusong Ju, Jianwei Zhu, Liang He, Bin Shao, Nanning Zheng, Tie-Yan Liu

NeurIPS 2021 Curriculum Offline Imitating Learning Minghuan Liu, Hanye Zhao, Zhengyu Yang, Jian Shen, Weinan Zhang, Li Zhao, Tie-Yan Liu

NeurIPS 2021 Distributional Reinforcement Learning for Multi-Dimensional Reward Functions Pushi Zhang, Xiaoyu Chen, Li Zhao, Wei Xiong, Tao Qin, Tie-Yan Liu

ICLR 2021 Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu

NeurIPS 2021 Do Transformers Really Perform Badly for Graph Representation? Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu

NeurIPS 2021 FastCorrect: Fast Error Correction with Edit Alignment for Automatic Speech Recognition Yichong Leng, Xu Tan, Linchen Zhu, Jin Xu, Renqian Luo, Linquan Liu, Tao Qin, Xiangyang Li, Edward Lin, Tie-Yan Liu

ICLR 2021 FastSpeech 2: Fast and High-Quality End-to-End Text to Speech Yi Ren, Chenxu Hu, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, Tie-Yan Liu

ICML 2021 GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang

ICML 2021 How Could Neural Networks Understand Programs? Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu

AAAI 2021 How Does Data Augmentation Affect Privacy in Machine Learning? Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu

ICLR 2021 IOT: Instance-Wise Layer Reordering for Transformer Structures Jinhua Zhu, Lijun Wu, Yingce Xia, Shufang Xie, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu

IJCAI 2021 Independence-Aware Advantage Estimation Pushi Zhang, Li Zhao, Guoqing Liu, Jiang Bian, Minlie Huang, Tao Qin, Tie-Yan Liu

ICML 2021 Large Scale Private Learning via Low-Rank Reparametrization Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu

NeurIPS 2021 Learning Causal Semantic Representation for Out-of-Distribution Prediction Chang Liu, Xinwei Sun, Jindong Wang, Haoyue Tang, Tao Li, Tao Qin, Wei Chen, Tie-Yan Liu

IJCAI 2021 MFVFD: A Multi-Agent Q-Learning Approach to Cooperative and Non-Cooperative Tasks Tianhao Zhang, Qiwei Ye, Jiang Bian, Guangming Xie, Tie-Yan Liu

NeurIPS 2021 Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning Jongjin Park, Younggyo Seo, Chang Liu, Li Zhao, Tao Qin, Jinwoo Shin, Tie-Yan Liu

NeurIPS 2021 On the Generative Utility of Cyclic Conditionals Chang Liu, Haoyue Tang, Tao Qin, Jintao Wang, Tie-Yan Liu

NeurIPS 2021 Optimizing Information-Theoretical Generalization Bound via Anisotropic Noise of SGLD Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu

UAI 2021 Path-BN: Towards Effective Batch Normalization in the Path Space for ReLU Networks Xufang Luo, Qi Meng, Wei Chen, Yunhong Wang, Tie-Yan Liu

NeurIPS 2021 R-Drop: Regularized Dropout for Neural Networks Xiaobo Liang, Lijun Wu, Juntao Li, Yue Wang, Qi Meng, Tao Qin, Wei Chen, Min Zhang, Tie-Yan Liu

NeurIPS 2021 Recovering Latent Causal Factor for Generalization to Distributional Shifts Xinwei Sun, Botong Wu, Xiangyu Zheng, Chang Liu, Wei Chen, Tao Qin, Tie-Yan Liu

ICLR 2021 Rethinking Positional Encoding in Language Pre-Training Guolin Ke, Di He, Tie-Yan Liu

ICLR 2021 Return-Based Contrastive Representation Learning for Reinforcement Learning Guoqing Liu, Chuheng Zhang, Li Zhao, Tao Qin, Jinhua Zhu, Li Jian, Nenghai Yu, Tie-Yan Liu

NeurIPS 2021 Speech-T: Transducer for Text to Speech and Beyond Jiawei Chen, Xu Tan, Yichong Leng, Jin Xu, Guihua Wen, Tao Qin, Tie-Yan Liu

NeurIPS 2021 Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu

NeurIPS 2021 Stylized Dialogue Generation with Multi-Pass Dual Learning Jinpeng Li, Yingce Xia, Rui Yan, Hongda Sun, Dongyan Zhao, Tie-Yan Liu

ICLR 2021 Taking Notes on the Fly Helps Language Pre-Training Qiyu Wu, Chen Xing, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu

ICML 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

ICML 2021 The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu

AAAI 2021 UWSpeech: Speech to Speech Translation for Unwritten Languages Chen Zhang, Xu Tan, Yi Ren, Tao Qin, Kejun Zhang, Tie-Yan Liu

AAAI 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

ACML 2020 Dual Learning: Theoretical Study and an Algorithmic Extension Zhibing Zhao, Yingce Xia, Tao Qin, Lirong Xia, Tie-Yan Liu

AAAI 2020 Fine-Tuning by Curriculum Learning for Non-Autoregressive Neural Machine Translation Junliang Guo, Xu Tan, Linli Xu, Tao Qin, Enhong Chen, Tie-Yan Liu

IJCAI 2020 Gradient Perturbation Is Underrated for Differentially Private Convex Optimization Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu

ICLR 2020 Incorporating BERT into Neural Machine Translation Jinhua Zhu, Yingce Xia, Lijun Wu, Di He, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu

ECCV 2020 Invertible Image Rescaling Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu

AAAI 2020 Light Multi-Segment Activation for Model Compression Zhenhui Xu, Guolin Ke, Jia Zhang, Jiang Bian, Tie-Yan Liu

NeurIPS 2020 MPNet: Masked and Permuted Pre-Training for Language Understanding Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, Tie-Yan Liu

NeurIPS 2020 RD$^2$: Reward Decomposition with Representation Decomposition Zichuan Lin, Derek Yang, Li Zhao, Tao Qin, Guangwen Yang, Tie-Yan Liu

NeurIPS 2020 Semi-Supervised Neural Architecture Search Renqian Luo, Xu Tan, Rui Wang, Tao Qin, Enhong Chen, Tie-Yan Liu

IJCAI 2020 Task-Level Curriculum Learning for Non-Autoregressive Neural Machine Translation Jinglin Liu, Yi Ren, Xu Tan, Chen Zhang, Tao Qin, Zhou Zhao, Tie-Yan Liu

AAAI 2020 Transductive Ensemble Learning for Neural Machine Translation Yiren Wang, Lijun Wu, Yingce Xia, Tao Qin, ChengXiang Zhai, Tie-Yan Liu

ICLR 2020 Understanding and Improving Transformer from a Multi-Particle Dynamic System Point of View Yiping Lu, Zhuohan Li, Di He, Zhiqing Sun, Bin Dong, Tao Qin, Liwei Wang, Tie-Yan Liu

ICLRW 2020 Understanding and Improving Transformer from a Multi-Particle Dynamic System Point of View. Yiping Lu, Zhuohan Li, Di He, Zhiqing Sun, Bin Dong, Tao Qin, Liwei Wang, Tie-yan Liu

ICML 2019 Adaptive Regret of Convex and Smooth Functions Lijun Zhang, Tie-Yan Liu, Zhi-Hua Zhou

ICML 2019 Almost Unsupervised Text to Speech and Automatic Speech Recognition Yi Ren, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, Tie-Yan Liu

IJCAI 2019 BN-Invariant Sharpness Regularizes the Training Model to Better Generalization Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

AAAI 2019 Capacity Control of ReLU Neural Networks by Basis-Path Norm Shuxin Zheng, Qi Meng, Huishuai Zhang, Wei Chen, Nenghai Yu, Tie-Yan Liu

NeurIPS 2019 Distributional Reward Decomposition for Reinforcement Learning Zichuan Lin, Li Zhao, Derek Yang, Tao Qin, Tie-Yan Liu, Guangwen Yang

NeurIPS 2019 FastSpeech: Fast, Robust and Controllable Text to Speech Yi Ren, Yangjun Ruan, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, Tie-Yan Liu

NeurIPS 2019 Fully Parameterized Quantile Function for Distributional Reinforcement Learning Derek Yang, Li Zhao, Zichuan Lin, Tao Qin, Jiang Bian, Tie-Yan Liu

ICLR 2019 G-SGD: Optimizing ReLU Neural Networks in Its Positively Scale-Invariant Space Qi Meng, Shuxin Zheng, Huishuai Zhang, Wei Chen, Qiwei Ye, Zhi-Ming Ma, Nenghai Yu, Tie-Yan Liu

ICML 2019 MASS: Masked Sequence to Sequence Pre-Training for Language Generation Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, Tie-Yan Liu

AAAI 2019 Modeling Local Dependence in Natural Language with Multi-Channel Recurrent Neural Networks Chang Xu, Weiran Huang, Hongwei Wang, Gang Wang, Tie-Yan Liu

ICLR 2019 Multi-Agent Dual Learning Yiren Wang, Yingce Xia, Tianyu He, Fei Tian, Tao Qin, ChengXiang Zhai, Tie-Yan Liu

ICLR 2019 Multilingual Neural Machine Translation with Knowledge Distillation Xu Tan, Yi Ren, Di He, Tao Qin, Zhou Zhao, Tie-Yan Liu

NeurIPS 2019 Neural Machine Translation with Soft Prototype Yiren Wang, Yingce Xia, Fei Tian, Fei Gao, Tao Qin, Cheng Xiang Zhai, Tie-Yan Liu

AAAI 2019 Non-Autoregressive Machine Translation with Auxiliary Regularization Yiren Wang, Fei Tian, Di He, Tao Qin, ChengXiang Zhai, Tie-Yan Liu

AAAI 2019 Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input Junliang Guo, Xu Tan, Di He, Tao Qin, Linli Xu, Tie-Yan Liu

NeurIPS 2019 Normalization Helps Training of Quantized LSTM Lu Hou, Jinhua Zhu, James Kwok, Fei Gao, Tao Qin, Tie-Yan Liu

IJCAI 2019 Polygon-Net: A General Framework for Jointly Boosting Multiple Unsupervised Neural Machine Translation Models Chang Xu, Tao Qin, Gang Wang, Tie-Yan Liu

AAAI 2019 Trust Region Evolution Strategies Guoqing Liu, Li Zhao, Feidiao Yang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu

ACML 2018 Adversarial Neural Machine Translation Lijun Wu, Yingce Xia, Fei Tian, Li Zhao, Tao Qin, Jianhuang Lai, Tie-Yan Liu

ACML 2018 Boosting Dynamic Programming with Neural Networks for Solving NP-Hard Problems Feidiao Yang, Tiancheng Jin, Tie-Yan Liu, Xiaoming Sun, Jialin Zhang

IJCAI 2018 Differential Equations for Modeling Asynchronous Algorithms Li He, Qi Meng, Wei Chen, Zhiming Ma, Tie-Yan Liu

AAAI 2018 Dual Transfer Learning for Neural Machine Translation with Marginal Distribution Regularization Yijun Wang, Yingce Xia, Li Zhao, Jiang Bian, Tao Qin, Guiquan Liu, Tie-Yan Liu

NeurIPS 2018 FRAGE: Frequency-Agnostic Word Representation Chengyue Gong, Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu

NeurIPS 2018 Layer-Wise Coordination Between Encoder and Decoder for Neural Machine Translation Tianyu He, Xu Tan, Yingce Xia, Di He, Tao Qin, Zhibo Chen, Tie-Yan Liu

ICLR 2018 Learning to Teach Yang Fan, Fei Tian, Tao Qin, Xiang-Yang Li, Tie-Yan Liu

NeurIPS 2018 Learning to Teach with Dynamic Loss Functions Lijun Wu, Fei Tian, Yingce Xia, Yang Fan, Tao Qin, Lai Jian-Huang, Tie-Yan Liu

ICML 2018 Model-Level Dual Learning Yingce Xia, Xu Tan, Fei Tian, Tao Qin, Nenghai Yu, Tie-Yan Liu

NeurIPS 2018 Neural Architecture Optimization Renqian Luo, Fei Tian, Tao Qin, Enhong Chen, Tie-Yan Liu

NeurIPS 2018 On the Local Hessian in Back-Propagation Huishuai Zhang, Wei Chen, Tie-Yan Liu

AAAI 2018 Word Attention for Sequence to Sequence Text Understanding Lijun Wu, Fei Tian, Li Zhao, Jianhuang Lai, Tie-Yan Liu

ICML 2017 Asynchronous Stochastic Gradient Descent with Delay Compensation Shuxin Zheng, Qi Meng, Taifeng Wang, Wei Chen, Nenghai Yu, Zhi-Ming Ma, Tie-Yan Liu

AAAI 2017 Asynchronous Stochastic Proximal Optimization Algorithms with Variance Reduction Qi Meng, Wei Chen, Jingcheng Yu, Taifeng Wang, Zhiming Ma, Tie-Yan Liu

NeurIPS 2017 Decoding with Value Networks for Neural Machine Translation Di He, Hanqing Lu, Yingce Xia, Tao Qin, Liwei Wang, Tie-Yan Liu

NeurIPS 2017 Deliberation Networks: Sequence Generation Beyond One-Pass Decoding Yingce Xia, Fei Tian, Lijun Wu, Jianxin Lin, Tao Qin, Nenghai Yu, Tie-Yan Liu

IJCAI 2017 Dual Inference for Machine Learning Yingce Xia, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu

ICML 2017 Dual Supervised Learning Yingce Xia, Tao Qin, Wei Chen, Jiang Bian, Nenghai Yu, Tie-Yan Liu

IJCAI 2017 Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems Quanming Yao, James T. Kwok, Fei Gao, Wei Chen, Tie-Yan Liu

IJCAI 2017 Efficient Mechanism Design for Online Scheduling (Extended Abstract) Xujin Chen, Xiaodong Hu, Tie-Yan Liu, Weidong Ma, Tao Qin, Pingzhong Tang, Changjun Wang, Bo Zheng

ECML-PKDD 2017 Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu

NeurIPS 2017 Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu

AAAI 2017 Generalization Error Bounds for Optimization Algorithms via Stability Qi Meng, Yue Wang, Wei Chen, Taifeng Wang, Zhiming Ma, Tie-Yan Liu

MLJ 2017 Introduction: Special Issue of Selected Papers from ACML 2015 Geoffrey Holmes, Tie-Yan Liu, Hang Li, Irwin King, Masashi Sugiyama, Zhi-Hua Zhou

NeurIPS 2017 LightGBM: A Highly Efficient Gradient Boosting Decision Tree Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, Tie-Yan Liu

AAAI 2017 Randomized Mechanisms for Selling Reserved Instances in Cloud Computing Jia Zhang, Weidong Ma, Tao Qin, Xiaoming Sun, Tie-Yan Liu

AAAI 2017 Revenue Maximization for Finitely Repeated Ad Auctions Jiang Rong, Tao Qin, Bo An, Tie-Yan Liu

ECML-PKDD 2017 Sequence Generation with Target Attention Yingce Xia, Fei Tian, Tao Qin, Nenghai Yu, Tie-Yan Liu

IJCAI 2017 Sequence Prediction with Unlabeled Data by Reward Function Learning Lijun Wu, Li Zhao, Tao Qin, Jianhuang Lai, Tie-Yan Liu

NeurIPS 2016 A Communication-Efficient Parallel Algorithm for Decision Tree Qi Meng, Guolin Ke, Taifeng Wang, Wei Chen, Qiwei Ye, Zhi-Ming Ma, Tie-Yan Liu

IJCAI 2016 Asynchronous Accelerated Stochastic Gradient Descent Qi Meng, Wei Chen, Jingcheng Yu, Taifeng Wang, Zhiming Ma, Tie-Yan Liu

IJCAI 2016 Budgeted Multi-Armed Bandits with Multiple Plays Yingce Xia, Tao Qin, Weidong Ma, Nenghai Yu, Tie-Yan Liu

NeurIPS 2016 Dual Learning for Machine Translation Di He, Yingce Xia, Tao Qin, Liwei Wang, Nenghai Yu, Tie-Yan Liu, Wei-Ying Ma

JAIR 2016 Efficient Mechanism Design for Online Scheduling Xujin Chen, Xiaodong Hu, Tie-Yan Liu, Weidong Ma, Tao Qin, Pingzhong Tang, Changjun Wang, Bo Zheng

NeurIPS 2016 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks Xiang Li, Tao Qin, Jian Yang, Tie-Yan Liu

AAAI 2016 On the Depth of Deep Neural Networks: A Theoretical View Shizhao Sun, Wei Chen, Liwei Wang, Xiaoguang Liu, Tie-Yan Liu

AAAI 2015 Generalization Analysis for Game-Theoretic Machine Learning Haifang Li, Fei Tian, Wei Chen, Tao Qin, Zhiming Ma, Tie-Yan Liu

AAAI 2015 Mechanism Learning with Mechanism Induced Data Tie-Yan Liu, Wei Chen, Tao Qin

IJCAI 2015 Optimal Pricing for the Competitive and Evolutionary Cloud Market Bolei Xu, Tao Qin, Guoping Qiu, Tie-Yan Liu

ACML 2015 Preface Geoffrey Holmes, Tie-Yan Liu

IJCAI 2015 Selling Reserved Instances in Cloud Computing Changjun Wang, Weidong Ma, Tao Qin, Xujin Chen, Xiaodong Hu, Tie-Yan Liu

IJCAI 2015 Thompson Sampling for Budgeted Multi-Armed Bandits Yingce Xia, Haifang Li, Tao Qin, Nenghai Yu, Tie-Yan Liu

AAAI 2014 Agent Behavior Prediction and Its Generalization Analysis Fei Tian, Haifang Li, Wei Chen, Tao Qin, Enhong Chen, Tie-Yan Liu

AAAI 2014 Incentivizing High-Quality Content from Heterogeneous Users: On the Existence of Nash Equilibrium Yingce Xia, Tao Qin, Nenghai Yu, Tie-Yan Liu

ECML-PKDD 2014 Knowledge-Powered Deep Learning for Word Embedding Jiang Bian, Bin Gao, Tie-Yan Liu

AAAI 2014 Learning Deep Representations for Graph Clustering Fei Tian, Bin Gao, Qing Cui, Enhong Chen, Tie-Yan Liu

AAAI 2014 Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks Yuyu Zhang, Hanjun Dai, Chang Xu, Jun Feng, Taifeng Wang, Jiang Bian, Bin Wang, Tie-Yan Liu

IJCAI 2013 A Game-Theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search Di He, Wei Chen, Liwei Wang, Tie-Yan Liu

COLT 2013 A Theoretical Analysis of NDCG Type Ranking Measures Yining Wang, Liwei Wang, Yuanzhi Li, Di He, Tie-Yan Liu

NeurIPS 2013 Estimation Bias in Multi-Armed Bandit Algorithms for Search Advertising Min Xu, Tao Qin, Tie-Yan Liu

AAAI 2013 Multi-Armed Bandit with Budget Constraint and Variable Costs Wenkui Ding, Tao Qin, Xu-Dong Zhang, Tie-Yan Liu

NeurIPS 2012 Statistical Consistency of Ranking Methods in a Rank-Differentiable Probability Space Yanyan Lan, Jiafeng Guo, Xueqi Cheng, Tie-yan Liu

NeurIPS 2010 A New Probabilistic Model for Rank Aggregation Tao Qin, Xiubo Geng, Tie-yan Liu

NeurIPS 2010 Two-Layer Generalization Analysis for Ranking Using Rademacher Average Wei Chen, Tie-yan Liu, Zhi-ming Ma

ICML 2009 Generalization Analysis of Listwise Learning-to-Rank Algorithms Yanyan Lan, Tie-Yan Liu, Zhiming Ma, Hang Li

NeurIPS 2009 Ranking Measures and Loss Functions in Learning to Rank Wei Chen, Tie-yan Liu, Yanyan Lan, Zhi-ming Ma, Hang Li

NeurIPS 2009 Statistical Consistency of Top-K Ranking Fen Xia, Tie-yan Liu, Hang Li

NeurIPS 2008 Global Ranking Using Continuous Conditional Random Fields Tao Qin, Tie-yan Liu, Xu-dong Zhang, De-sheng Wang, Hang Li

ICML 2008 Listwise Approach to Learning to Rank: Theory and Algorithm Fen Xia, Tie-Yan Liu, Jue Wang, Wensheng Zhang, Hang Li

ICML 2008 Query-Level Stability and Generalization in Learning to Rank Yanyan Lan, Tie-Yan Liu, Tao Qin, Zhiming Ma, Hang Li

ICML 2007 Learning to Rank: From Pairwise Approach to Listwise Approach Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, Hang Li

ECML-PKDD 2006 Fast Spectral Clustering of Data Using Sequential Matrix Compression Bo Chen, Bin Gao, Tie-Yan Liu, Yu-Fu Chen, Wei-Ying Ma