Tie-Yan Liu
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
217
Venues
32
Active years
2001–2024
Best venue rank
A*
Where they publish
- A*AAAI29 papers
- A*ICML26 papers
- A*ICLR23 papers
- A*IJCAI19 papers
- A*KDD19 papers
- A*SIGIR15 papers
- A*ACL13 papers
- A*WWW11 papers
- A*EMNLP10 papers
- ACIKM7 papers
- AWSDM5 papers
- BCOLING4 papers
- ANAACL4 papers
- CACML4 papers
- AInterspeech3 papers
- MulticonferenceICASSP3 papers
- A*CVPR2 papers
- AECIR2 papers
- A*ICDM2 papers
- BPAKDD2 papers
- BMMM2 papers
- BICIP2 papers
- AAISTATS1 paper
- AUAI1 paper
- A*ECCV1 paper
- A*ICDE1 paper
- CASRU1 paper
- AECAI1 paper
- UnrankedICTIR1 paper
- A*COLT1 paper
- CAPWEB1 paper
- CISCAS1 paper
Papers
217 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2024 | AAAI | Regeneration Learning: A Learning Paradigm for Data Generation. | Xu Tan, Tao Qin, Jiang Bian, Tie-Yan Liu, Yoshua Bengio |
| 2024 | ICLR | 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 |
| 2024 | ICML | GeoMFormer: A General Architecture for Geometric Molecular Representation Learning. | Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang |
| 2024 | ICML | 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 |
| 2024 | IJCAI | Re-creation of Creations: A New Paradigm for Lyric-to-Melody Generation. | Ang Lv, Xu Tan, Tao Qin, Tie-Yan Liu, Rui Yan |
| 2024 | KDD | Provable Adaptivity of Adam under Non-uniform Smoothness. | Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Ruoyu Sun, Zhi-Ming Ma, Tie-Yan Liu, Zhi-Quan Luo, Wei Chen |
| 2023 | AAAI | 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 |
| 2023 | AAAI | 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 |
| 2023 | AAAI | 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 |
| 2023 | ACL | MolXPT: Wrapping Molecules with Text for Generative Pre-training. | Zequn Liu, Wei Zhang, Yingce Xia, Lijun Wu, Shufang Xie, Tao Qin, Ming Zhang, Tie-Yan Liu |
| 2023 | ACL | Extract and Attend: Improving Entity Translation in Neural Machine Translation. | Zixin Zeng, Rui Wang, Yichong Leng, Junliang Guo, Shufang Xie, Xu Tan, Tao Qin, Tie-Yan Liu |
| 2023 | AISTATS | 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 |
| 2023 | ICLR | 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 |
| 2023 | ICLR | One Transformer Can Understand Both 2D & 3D Molecular Data. | Shengjie Luo, Tianlang Chen, Yixian Xu, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He |
| 2023 | ICLR | Making Better Decision by Directly Planning in Continuous Control. | Jinhua Zhu, Yue Wang, Lijun Wu, Tao Qin, Wengang Zhou, Tie-Yan Liu, Houqiang Li |
| 2023 | ICLR | 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 |
| 2023 | ICML | 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 |
| 2023 | ICML | Retrosynthetic Planning with Dual Value Networks. | Guoqing Liu, Di Xue, Shufang Xie, Yingce Xia, Austin Tripp, Krzysztof Maziarz, Marwin H. S. Segler, Tao Qin, Zongzhang Zhang, Tie-Yan Liu |
| 2023 | KDD | Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance. | Yuchen Fang, Zhenggang Tang, Kan Ren, Weiqing Liu, Li Zhao, Jiang Bian, Dongsheng Li, Weinan Zhang, Yong Yu, Tie-Yan Liu |
| 2023 | KDD | Pre-training Antibody Language Models for Antigen-Specific Computational Antibody Design. | Kaiyuan Gao, Lijun Wu, Jinhua Zhu, Tianbo Peng, Yingce Xia, Liang He, Shufang Xie, Tao Qin, Haiguang Liu, Kun He, Tie-Yan Liu |
| 2023 | KDD | Web-based Long-term Spine Treatment Outcome Forecasting. | Hangting Ye, Zhining Liu, Wei Cao, Amir M. Amiri, Jiang Bian, Yi Chang, Jon D. Lurie, Jim Weinstein, Tie-Yan Liu |
| 2023 | KDD | Dual-view Molecular Pre-training. | Jinhua Zhu, Yingce Xia, Lijun Wu, Shufang Xie, Wengang Zhou, Tao Qin, Houqiang Li, Tie-Yan Liu |
| 2022 | ACL | Revisiting Over-Smoothness in Text to Speech. | Yi Ren, Xu Tan, Tao Qin, Zhou Zhao, Tie-Yan Liu |
| 2022 | ACL | ProphetChat: Enhancing Dialogue Generation with Simulation of Future Conversation. | Chang Liu, Xu Tan, Chongyang Tao, Zhenxin Fu, Dongyan Zhao, Tie-Yan Liu, Rui Yan |
| 2022 | ACL | Finding the Dominant Winning Ticket in Pre-Trained Language Models. | Zhuocheng Gong, Di He, Yelong Shen, Tie-Yan Liu, Weizhu Chen, Dongyan Zhao, Ji-Rong Wen, Rui Yan |
| 2022 | COLING | KGE-CL: Contrastive Learning of Tensor Decomposition Based Knowledge Graph Embeddings. | Zhiping Luo, Wentao Xu, Weiqing Liu, Jiang Bian, Jian Yin, Tie-Yan Liu |
| 2022 | CVPR | 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 |
| 2022 | EMNLP | TeleMelody: Lyric-to-Melody Generation with a Template-Based Two-Stage Method. | Zeqian Ju, Peiling Lu, Xu Tan, Rui Wang, Chen Zhang, Songruoyao Wu, Kejun Zhang, Xiang-Yang Li, Tao Qin, Tie-Yan Liu |
| 2022 | ICLR | Target-Side Input Augmentation for Sequence to Sequence Generation. | Shufang Xie, Ang Lv, Yingce Xia, Lijun Wu, Tao Qin, Tie-Yan Liu, Rui Yan |
| 2022 | ICLR | DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting. | Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu |
| 2022 | ICLR | Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality. | Jiawei Huang, Jinglin Chen, Li Zhao, Tao Qin, Nan Jiang, Tie-Yan Liu |
| 2022 | ICLR | 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 |
| 2022 | ICLR | 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 |
| 2022 | ICML | 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 |
| 2022 | ICML | Supervised Off-Policy Ranking. | Yue Jin, Yue Zhang, Tao Qin, Xudong Zhang, Jian Yuan, Houqiang Li, Tie-Yan Liu |
| 2022 | ICML | 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 |
| 2022 | Interspeech | AdaSpeech 4: Adaptive Text to Speech in Zero-Shot Scenarios. | Yihan Wu, Xu Tan, Bohan Li, Lei He, Sheng Zhao, Ruihua Song, Tao Qin, Tie-Yan Liu |
| 2022 | KDD | Availability Attacks Create Shortcuts. | Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu |
| 2022 | KDD | Unified 2D and 3D Pre-Training of Molecular Representations. | Jinhua Zhu, Yingce Xia, Lijun Wu, Shufang Xie, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu |
| 2022 | NAACL | A Study of Syntactic Multi-Modality in Non-Autoregressive Machine Translation. | Kexun Zhang, Rui Wang, Xu Tan, Junliang Guo, Yi Ren, Tao Qin, Tie-Yan Liu |
| 2021 | AAAI | 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 |
| 2021 | AAAI | How Does Data Augmentation Affect Privacy in Machine Learning? | Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu |
| 2021 | AAAI | UWSpeech: Speech to Speech Translation for Unwritten Languages. | Chen Zhang, Xu Tan, Yi Ren, Tao Qin, Kejun Zhang, Tie-Yan Liu |
| 2021 | ACL | DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modeling. | Lanqing Xue, Kaitao Song, Duocai Wu, Xu Tan, Nevin L. Zhang, Tao Qin, Wei-Qiang Zhang, Tie-Yan Liu |
| 2021 | ACL | MusicBERT: Symbolic Music Understanding with Large-Scale Pre-Training. | Mingliang Zeng, Xu Tan, Rui Wang, Zeqian Ju, Tao Qin, Tie-Yan Liu |
| 2021 | CIKM | Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion. | Min Hou, Chang Xu, Yang Liu, Weiqing Liu, Jiang Bian, Le Wu, Zhi Li, Enhong Chen, Tie-Yan Liu |
| 2021 | CIKM | HierST: A Unified Hierarchical Spatial-temporal Framework for COVID-19 Trend Forecasting. | Shun Zheng, Zhifeng Gao, Wei Cao, Jiang Bian, Tie-Yan Liu |
| 2021 | EMNLP | FastCorrect 2: Fast Error Correction on Multiple Candidates for Automatic Speech Recognition. | Yichong Leng, Xu Tan, Rui Wang, Linchen Zhu, Jin Xu, Wenjie Liu, Linquan Liu, Xiang-Yang Li, Tao Qin, Edward Lin, Tie-Yan Liu |
| 2021 | EMNLP | Less is More: Pretrain a Strong Siamese Encoder for Dense Text Retrieval Using a Weak Decoder. | Shuqi Lu, Di He, Chenyan Xiong, Guolin Ke, Waleed Malik, Zhicheng Dou, Paul Bennett, Tie-Yan Liu, Arnold Overwijk |
| 2021 | ICASSP | Lightspeech: Lightweight and Fast Text to Speech with Neural Architecture Search. | Renqian Luo, Xu Tan, Rui Wang, Tao Qin, Jinzhu Li, Sheng Zhao, Enhong Chen, Tie-Yan Liu |
| 2021 | ICASSP | Adaspeech 2: Adaptive Text to Speech with Untranscribed Data. | Yuzi Yan, Xu Tan, Bohan Li, Tao Qin, Sheng Zhao, Yuan Shen, Tie-Yan Liu |
| 2021 | ICASSP | Denoispeech: Denoising Text to Speech with Frame-Level Noise Modeling. | Chen Zhang, Yi Ren, Xu Tan, Jinglin Liu, Kejun Zhang, Tao Qin, Sheng Zhao, Tie-Yan Liu |
| 2021 | ICLR | Taking Notes on the Fly Helps Language Pre-Training. | Qiyu Wu, Chen Xing, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu |
| 2021 | ICLR | 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 |
| 2021 | ICLR | AdaSpeech: Adaptive Text to Speech for Custom Voice. | Mingjian Chen, Xu Tan, Bohan Li, Yanqing Liu, Tao Qin, Sheng Zhao, Tie-Yan Liu |
| 2021 | ICLR | Rethinking Positional Encoding in Language Pre-training. | Guolin Ke, Di He, Tie-Yan Liu |
| 2021 | ICLR | Return-Based Contrastive Representation Learning for Reinforcement Learning. | Guoqing Liu, Chuheng Zhang, Li Zhao, Tao Qin, Jinhua Zhu, Jian Li, Nenghai Yu, Tie-Yan Liu |
| 2021 | ICLR | Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning. | Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu |
| 2021 | ICLR | 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 |
| 2021 | ICML | GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training. | Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang |
| 2021 | ICML | How could Neural Networks understand Programs? | Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu |
| 2021 | ICML | The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks. | Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu |
| 2021 | ICML | 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 | ICML | Large Scale Private Learning via Low-rank Reparametrization. | Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu |
| 2021 | IJCAI | A Survey on Low-Resource Neural Machine Translation. | Rui Wang, Xu Tan, Renqian Luo, Tao Qin, Tie-Yan Liu |
| 2021 | IJCAI | MFVFD: A Multi-Agent Q-Learning Approach to Cooperative and Non-Cooperative Tasks. | Tianhao Zhang, Qiwei Ye, Jiang Bian, Guangming Xie, Tie-Yan Liu |
| 2021 | IJCAI | Independence-aware Advantage Estimation. | Pushi Zhang, Li Zhao, Guoqing Liu, Jiang Bian, Minlie Huang, Tao Qin, Tie-Yan Liu |
| 2021 | Interspeech | Adaptive Text to Speech for Spontaneous Style. | Yuzi Yan, Xu Tan, Bohan Li, Guangyan Zhang, Tao Qin, Sheng Zhao, Yuan Shen, Wei-Qiang Zhang, Tie-Yan Liu |
| 2021 | KDD | NAS-BERT: Task-Agnostic and Adaptive-Size BERT Compression with Neural Architecture Search. | Jin Xu, Xu Tan, Renqian Luo, Kaitao Song, Jian Li, Tao Qin, Tie-Yan Liu |
| 2021 | NAACL | UniDrop: A Simple yet Effective Technique to Improve Transformer without Extra Cost. | Zhen Wu, Lijun Wu, Qi Meng, Yingce Xia, Shufang Xie, Tao Qin, Xinyu Dai, Tie-Yan Liu |
| 2021 | WWW | REST: Relational Event-driven Stock Trend Forecasting. | Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu |
| 2021 | UAI | Path-BN: Towards effective batch normalization in the Path Space for ReLU networks. | Xufang Luo, Qi Meng, Wei Chen, Yunhong Wang, Tie-Yan Liu |
| 2020 | AAAI | Fine-Tuning by Curriculum Learning for Non-Autoregressive Neural Machine Translation. | Junliang Guo, Xu Tan, Linli Xu, Tao Qin, Enhong Chen, Tie-Yan Liu |
| 2020 | AAAI | Transductive Ensemble Learning for Neural Machine Translation. | Yiren Wang, Lijun Wu, Yingce Xia, Tao Qin, ChengXiang Zhai, Tie-Yan Liu |
| 2020 | AAAI | Light Multi-Segment Activation for Model Compression. | Zhenhui Xu, Guolin Ke, Jia Zhang, Jiang Bian, Tie-Yan Liu |
| 2020 | ACL | SimulSpeech: End-to-End Simultaneous Speech to Text Translation. | Yi Ren, Jinglin Liu, Xu Tan, Chen Zhang, Tao Qin, Zhou Zhao, Tie-Yan Liu |
| 2020 | ACL | A Study of Non-autoregressive Model for Sequence Generation. | Yi Ren, Jinglin Liu, Xu Tan, Zhou Zhao, Sheng Zhao, Tie-Yan Liu |
| 2020 | ACL | SEEK: Segmented Embedding of Knowledge Graphs. | Wentao Xu, Shun Zheng, Liang He, Bin Shao, Jian Yin, Tie-Yan Liu |
| 2020 | ACML | Dual Learning: Theoretical Study and an Algorithmic Extension. | Zhibing Zhao, Yingce Xia, Tao Qin, Lirong Xia, Tie-Yan Liu |
| 2020 | ECCV | Invertible Image Rescaling. | Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu |
| 2020 | ICDE | Self-paced Ensemble for Highly Imbalanced Massive Data Classification. | Zhining Liu, Wei Cao, Zhifeng Gao, Jiang Bian, Hechang Chen, Yi Chang, Tie-Yan Liu |
| 2020 | ICLR | Incorporating BERT into Neural Machine Translation. | Jinhua Zhu, Yingce Xia, Lijun Wu, Di He, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu |
| 2020 | ICML | Sequence Generation with Mixed Representations. | Lijun Wu, Shufang Xie, Yingce Xia, Yang Fan, Jian-Huang Lai, Tao Qin, Tie-Yan Liu |
| 2020 | ICML | On Layer Normalization in the Transformer Architecture. | Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tie-Yan Liu |
| 2020 | IJCAI | 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 |
| 2020 | IJCAI | Gradient Perturbation is Underrated for Differentially Private Convex Optimization. | Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu |
| 2020 | KDD | DeepSinger: Singing Voice Synthesis with Data Mined From the Web. | Yi Ren, Xu Tan, Tao Qin, Jian Luan, Zhou Zhao, Tie-Yan Liu |
| 2020 | KDD | LRSpeech: Extremely Low-Resource Speech Synthesis and Recognition. | Jin Xu, Xu Tan, Yi Ren, Tao Qin, Jian Li, Sheng Zhao, Tie-Yan Liu |
| 2019 | AAAI | Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input. | Junliang Guo, Xu Tan, Di He, Tao Qin, Linli Xu, Tie-Yan Liu |
| 2019 | AAAI | Trust Region Evolution Strategies. | Guoqing Liu, Li Zhao, Feidiao Yang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu |
| 2019 | AAAI | Non-Autoregressive Machine Translation with Auxiliary Regularization. | Yiren Wang, Fei Tian, Di He, Tao Qin, ChengXiang Zhai, Tie-Yan Liu |
| 2019 | AAAI | Modeling Local Dependence in Natural Language with Multi-Channel Recurrent Neural Networks. | Chang Xu, Weiran Huang, Hongwei Wang, Gang Wang, Tie-Yan Liu |
| 2019 | AAAI | Capacity Control of ReLU Neural Networks by Basis-Path Norm. | Shuxin Zheng, Qi Meng, Huishuai Zhang, Wei Chen, Nenghai Yu, Tie-Yan Liu |
| 2019 | ACL | Soft Contextual Data Augmentation for Neural Machine Translation. | Fei Gao, Jinhua Zhu, Lijun Wu, Yingce Xia, Tao Qin, Xueqi Cheng, Wengang Zhou, Tie-Yan Liu |
| 2019 | ACL | Unsupervised Pivot Translation for Distant Languages. | Yichong Leng, Xu Tan, Tao Qin, Xiang-Yang Li, Tie-Yan Liu |
| 2019 | ACL | Depth Growing for Neural Machine Translation. | Lijun Wu, Yiren Wang, Yingce Xia, Fei Tian, Fei Gao, Tao Qin, Jianhuang Lai, Tie-Yan Liu |
| 2019 | ASRU | Knowledge Distillation from Bert in Pre-Training and Fine-Tuning for Polyphone Disambiguation. | Hao Sun, Xu Tan, Jun-Wei Gan, Sheng Zhao, Dongxu Han, Hongzhi Liu, Tao Qin, Tie-Yan Liu |
| 2019 | EMNLP | Hint-Based Training for Non-Autoregressive Machine Translation. | Zhuohan Li, Zi Lin, Di He, Fei Tian, Tao Qin, Liwei Wang, Tie-Yan Liu |
| 2019 | EMNLP | Multilingual Neural Machine Translation with Language Clustering. | Xu Tan, Jiale Chen, Di He, Yingce Xia, Tao Qin, Tie-Yan Liu |
| 2019 | EMNLP | Exploiting Monolingual Data at Scale for Neural Machine Translation. | Lijun Wu, Yiren Wang, Yingce Xia, Tao Qin, Jianhuang Lai, Tie-Yan Liu |
| 2019 | EMNLP | Machine Translation With Weakly Paired Documents. | Lijun Wu, Jinhua Zhu, Di He, Fei Gao, Tao Qin, Jianhuang Lai, Tie-Yan Liu |
| 2019 | ICLR | Representation Degeneration Problem in Training Natural Language Generation Models. | Jun Gao, Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu |
| 2019 | ICLR | 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 |
| 2019 | ICLR | Multilingual Neural Machine Translation with Knowledge Distillation. | Xu Tan, Yi Ren, Di He, Tao Qin, Zhou Zhao, Tie-Yan Liu |
| 2019 | ICLR | Multi-Agent Dual Learning. | Yiren Wang, Yingce Xia, Tianyu He, Fei Tian, Tao Qin, ChengXiang Zhai, Tie-Yan Liu |
| 2019 | ICML | Efficient Training of BERT by Progressively Stacking. | Linyuan Gong, Di He, Zhuohan Li, Tao Qin, Liwei Wang, Tie-Yan Liu |
| 2019 | ICML | Almost Unsupervised Text to Speech and Automatic Speech Recognition. | Yi Ren, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, Tie-Yan Liu |
| 2019 | ICML | MASS: Masked Sequence to Sequence Pre-training for Language Generation. | Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, Tie-Yan Liu |
| 2019 | ICML | Adaptive Regret of Convex and Smooth Functions. | Lijun Zhang, Tie-Yan Liu, Zhi-Hua Zhou |
| 2019 | IJCAI | Polygon-Net: A General Framework for Jointly Boosting Multiple Unsupervised Neural Machine Translation Models. | Chang Xu, Tao Qin, Gang Wang, Tie-Yan Liu |
| 2019 | IJCAI | BN-invariant Sharpness Regularizes the Training Model to Better Generalization. | Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu |
| 2019 | Interspeech | Token-Level Ensemble Distillation for Grapheme-to-Phoneme Conversion. | Hao Sun, Xu Tan, Jun-Wei Gan, Hongzhi Liu, Sheng Zhao, Tao Qin, Tie-Yan Liu |
| 2019 | KDD | Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction. | Chi Chen, Li Zhao, Jiang Bian, Chunxiao Xing, Tie-Yan Liu |
| 2019 | KDD | DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks. | Guolin Ke, Zhenhui Xu, Jia Zhang, Jiang Bian, Tie-Yan Liu |
| 2019 | KDD | Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding. | Zhige Li, Derek Yang, Li Zhao, Jiang Bian, Tao Qin, Tie-Yan Liu |
| 2018 | AAAI | 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 |
| 2018 | AAAI | Word Attention for Sequence to Sequence Text Understanding. | Lijun Wu, Fei Tian, Li Zhao, Jianhuang Lai, Tie-Yan Liu |
| 2018 | ACML | Adversarial Neural Machine Translation. | Lijun Wu, Yingce Xia, Fei Tian, Li Zhao, Tao Qin, Jianhuang Lai, Tie-Yan Liu |
| 2018 | ACML | Boosting Dynamic Programming with Neural Networks for Solving NP-hard Problems. | Feidiao Yang, Tiancheng Jin, Tie-Yan Liu, Xiaoming Sun, Jialin Zhang |
| 2018 | COLING | Double Path Networks for Sequence to Sequence Learning. | Kaitao Song, Xu Tan, Di He, Jianfeng Lu, Tao Qin, Tie-Yan Liu |
| 2018 | CVPR | Conditional Image-to-Image Translation. | Jianxin Lin, Yingce Xia, Tao Qin, Zhibo Chen, Tie-Yan Liu |
| 2018 | EMNLP | Beyond Error Propagation in Neural Machine Translation: Characteristics of Language Also Matter. | Lijun Wu, Xu Tan, Di He, Fei Tian, Tao Qin, Jianhuang Lai, Tie-Yan Liu |
| 2018 | EMNLP | A Study of Reinforcement Learning for Neural Machine Translation. | Lijun Wu, Fei Tian, Tao Qin, Jianhuang Lai, Tie-Yan Liu |
| 2018 | ICLR | Learning to Teach. | Yang Fan, Fei Tian, Tao Qin, Xiang-Yang Li, Tie-Yan Liu |
| 2018 | ICML | Towards Binary-Valued Gates for Robust LSTM Training. | Zhuohan Li, Di He, Fei Tian, Wei Chen, Tao Qin, Liwei Wang, Tie-Yan Liu |
| 2018 | ICML | Model-Level Dual Learning. | Yingce Xia, Xu Tan, Fei Tian, Tao Qin, Nenghai Yu, Tie-Yan Liu |
| 2018 | IJCAI | Differential Equations for Modeling Asynchronous Algorithms. | Li He, Qi Meng, Wei Chen, Zhiming Ma, Tie-Yan Liu |
| 2018 | KDD | Investor-Imitator: A Framework for Trading Knowledge Extraction. | Yi Ding, Weiqing Liu, Jiang Bian, Daoqiang Zhang, Tie-Yan Liu |
| 2018 | NAACL | Efficient Sequence Learning with Group Recurrent Networks. | Fei Gao, Lijun Wu, Li Zhao, Tao Qin, Xueqi Cheng, Tie-Yan Liu |
| 2018 | NAACL | Dense Information Flow for Neural Machine Translation. | Yanyao Shen, Xu Tan, Di He, Tao Qin, Tie-Yan Liu |
| 2018 | SIGIR | Towards Better Text Understanding and Retrieval through Kernel Entity Salience Modeling. | Chenyan Xiong, Zhengzhong Liu, Jamie Callan, Tie-Yan Liu |
| 2018 | WSDM | Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction. | Ziniu Hu, Weiqing Liu, Jiang Bian, Xuanzhe Liu, Tie-Yan Liu |
| 2017 | AAAI | Asynchronous Stochastic Proximal Optimization Algorithms with Variance Reduction. | Qi Meng, Wei Chen, Jingcheng Yu, Taifeng Wang, Zhiming Ma, Tie-Yan Liu |
| 2017 | AAAI | Generalization Error Bounds for Optimization Algorithms via Stability. | Qi Meng, Yue Wang, Wei Chen, Taifeng Wang, Zhiming Ma, Tie-Yan Liu |
| 2017 | AAAI | Revenue Maximization for Finitely Repeated Ad Auctions. | Jiang Rong, Tao Qin, Bo An, Tie-Yan Liu |
| 2017 | AAAI | Randomized Mechanisms for Selling Reserved Instances in Cloud Computing. | Jia Zhang, Weidong Ma, Tao Qin, Xiaoming Sun, Tie-Yan Liu |
| 2017 | ICML | Dual Supervised Learning. | Yingce Xia, Tao Qin, Wei Chen, Jiang Bian, Nenghai Yu, Tie-Yan Liu |
| 2017 | ICML | Asynchronous Stochastic Gradient Descent with Delay Compensation. | Shuxin Zheng, Qi Meng, Taifeng Wang, Wei Chen, Nenghai Yu, Zhiming Ma, Tie-Yan Liu |
| 2017 | IJCAI | 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 |
| 2017 | IJCAI | Sequence Prediction with Unlabeled Data by Reward Function Learning. | Lijun Wu, Li Zhao, Tao Qin, Jianhuang Lai, Tie-Yan Liu |
| 2017 | IJCAI | Dual Inference for Machine Learning. | Yingce Xia, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu |
| 2017 | IJCAI | Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems. | Quanming Yao, James T. Kwok, Fei Gao, Wei Chen, Tie-Yan Liu |
| 2017 | WWW | Distributed Machine Learning: Foundations, Trends, and Practices. | Tie-Yan Liu, Wei Chen, Taifeng Wang |
| 2017 | SIGIR | Word-Entity Duet Representations for Document Ranking. | Chenyan Xiong, Jamie Callan, Tie-Yan Liu |
| 2016 | AAAI | On the Depth of Deep Neural Networks: A Theoretical View. | Shizhao Sun, Wei Chen, Liwei Wang, Xiaoguang Liu, Tie-Yan Liu |
| 2016 | ECAI | Modeling Bounded Rationality for Sponsored Search Auctions. | Jiang Rong, Tao Qin, Bo An, Tie-Yan Liu |
| 2016 | EMNLP | Solving Verbal Questions in IQ Test by Knowledge-Powered Word Embedding. | Huazheng Wang, Fei Tian, Bin Gao, Chengjieren Zhu, Jiang Bian, Tie-Yan Liu |
| 2016 | IJCAI | Asynchronous Accelerated Stochastic Gradient Descent. | Qi Meng, Wei Chen, Jingcheng Yu, Taifeng Wang, Zhiming Ma, Tie-Yan Liu |
| 2016 | IJCAI | Budgeted Multi-Armed Bandits with Multiple Plays. | Yingce Xia, Tao Qin, Weidong Ma, Nenghai Yu, Tie-Yan Liu |
| 2016 | ICTIR | Bag-of-Entities Representation for Ranking. | Chenyan Xiong, Jamie Callan, Tie-Yan Liu |
| 2015 | AAAI | Generalization Analysis for Game-Theoretic Machine Learning. | Haifang Li, Fei Tian, Wei Chen, Tao Qin, Zhiming Ma, Tie-Yan Liu |
| 2015 | AAAI | Mechanism Learning with Mechanism Induced Data. | Tie-Yan Liu, Wei Chen, Tao Qin |
| 2015 | ACML | Preface. | Geoffrey Holmes, Tie-Yan Liu |
| 2015 | IJCAI | Selling Reserved Instances in Cloud Computing. | Changjun Wang, Weidong Ma, Tao Qin, Xujin Chen, Xiaodong Hu, Tie-Yan Liu |
| 2015 | IJCAI | Thompson Sampling for Budgeted Multi-Armed Bandits. | Yingce Xia, Haifang Li, Tao Qin, Nenghai Yu, Tie-Yan Liu |
| 2015 | IJCAI | Optimal Pricing for the Competitive and Evolutionary Cloud Market. | Bolei Xu, Tao Qin, Guoping Qiu, Tie-Yan Liu |
| 2015 | WWW | LightLDA: Big Topic Models on Modest Computer Clusters. | Jinhui Yuan, Fei Gao, Qirong Ho, Wei Dai, Jinliang Wei, Xun Zheng, Eric Poe Xing, Tie-Yan Liu, Wei-Ying Ma |
| 2015 | SIGIR | Listwise Collaborative Filtering. | Shanshan Huang, Shuaiqiang Wang, Tie-Yan Liu, Jun Ma, Zhumin Chen, Jari Veijalainen |
| 2014 | AAAI | Learning Deep Representations for Graph Clustering. | Fei Tian, Bin Gao, Qing Cui, Enhong Chen, Tie-Yan Liu |
| 2014 | AAAI | Agent Behavior Prediction and Its Generalization Analysis. | Fei Tian, Haifang Li, Wei Chen, Tao Qin, Enhong Chen, Tie-Yan Liu |
| 2014 | AAAI | Incentivizing High-Quality Content from Heterogeneous Users: On the Existence of Nash Equilibrium. | Yingce Xia, Tao Qin, Nenghai Yu, Tie-Yan Liu |
| 2014 | AAAI | 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 |
| 2014 | CIKM | RC-NET: A General Framework for Incorporating Knowledge into Word Representations. | Chang Xu, Yalong Bai, Jiang Bian, Bin Gao, Gang Wang, Xiaoguang Liu, Tie-Yan Liu |
| 2014 | COLING | Co-learning of Word Representations and Morpheme Representations. | Siyu Qiu, Qing Cui, Jiang Bian, Bin Gao, Tie-Yan Liu |
| 2014 | COLING | A Probabilistic Model for Learning Multi-Prototype Word Embeddings. | Fei Tian, Hanjun Dai, Jiang Bian, Bin Gao, Rui Zhang, Enhong Chen, Tie-Yan Liu |
| 2014 | WSDM | Sampling dilemma: towards effective data sampling for click prediction in sponsored search. | Jun Feng, Jiang Bian, Taifeng Wang, Wei Chen, Xiaoyan Zhu, Tie-Yan Liu |
| 2013 | AAAI | Multi-Armed Bandit with Budget Constraint and Variable Costs. | Wenkui Ding, Tao Qin, Xu-Dong Zhang, Tie-Yan Liu |
| 2013 | COLT | A Theoretical Analysis of NDCG Type Ranking Measures. | Yining Wang, Liwei Wang, Yuanzhi Li, Di He, Tie-Yan Liu |
| 2013 | IJCAI | A Game-Theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search. | Di He, Wei Chen, Liwei Wang, Tie-Yan Liu |
| 2013 | KDD | Psychological advertising: exploring user psychology for click prediction in sponsored search. | Taifeng Wang, Jiang Bian, Shusen Liu, Yuyu Zhang, Tie-Yan Liu |
| 2013 | WWW | Predicting advertiser bidding behaviors in sponsored search by rationality modeling. | Haifeng Xu, Bin Gao, Diyi Yang, Tie-Yan Liu |
| 2013 | SIGIR | Internet advertising: theory and practice. | Bin Gao, Jun Yan, Dou Shen, Tie-Yan Liu |
| 2012 | CIKM | A unified optimization framework for auction and guaranteed delivery in online advertising. | Konstantin Salomatin, Tie-Yan Liu, Yiming Yang |
| 2012 | KDD | Joint optimization of bid and budget allocation in sponsored search. | Weinan Zhang, Ying Zhang, Bin Gao, Yong Yu, Xiaojie Yuan, Tie-Yan Liu |
| 2012 | SIGIR | Large-scale graph mining and learning for information retrieval. | Bin Gao, Taifeng Wang, Tie-Yan Liu |
| 2012 | WSDM | Relational click prediction for sponsored search. | Chenyan Xiong, Taifeng Wang, Wenkui Ding, Yidong Shen, Tie-Yan Liu |
| 2011 | CIKM | Advertiser-centric approach to understand user click behavior in sponsored search. | Sungchul Kim, Tao Qin, Hwanjo Yu, Tie-Yan Liu |
| 2011 | KDD | Semi-supervised ranking on very large graphs with rich metadata. | Bin Gao, Tie-Yan Liu, Wei Wei, Taifeng Wang, Hang Li |
| 2011 | WWW | Ranking on large-scale graphs with rich metadata. | Bin Gao, Taifeng Wang, Tie-Yan Liu |
| 2011 | WSDM | Let web spammers expose themselves. | Zhicong Cheng, Bin Gao, Congkai Sun, Yanbing Jiang, Tie-Yan Liu |
| 2010 | WWW | Actively predicting diverse search intent from user browsing behaviors. | Zhicong Cheng, Bin Gao, Tie-Yan Liu |
| 2010 | SIGIR | Learning to rank for information retrieval. | Tie-Yan Liu |
| 2010 | WSDM | Ranking with query-dependent loss for web search. | Jiang Bian, Tie-Yan Liu, Tao Qin, Hongyuan Zha |
| 2009 | CIKM | A general markov framework for page importance computation. | Bin Gao, Tie-Yan Liu, Zhiming Ma, Taifeng Wang, Hang Li |
| 2009 | ICML | Generalization analysis of listwise learning-to-rank algorithms. | Yanyan Lan, Tie-Yan Liu, Zhiming Ma, Hang Li |
| 2008 | ICML | Query-level stability and generalization in learning to rank. | Yanyan Lan, Tie-Yan Liu, Tao Qin, Zhiming Ma, Hang Li |
| 2008 | ICML | Listwise approach to learning to rank: theory and algorithm. | Fen Xia, Tie-Yan Liu, Jue Wang, Wensheng Zhang, Hang Li |
| 2008 | WWW | Learning to rank relational objects and its application to web search. | Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang, Wen-Ying Xiong, Hang Li |
| 2008 | SIGIR | Query dependent ranking using K-nearest neighbor. | Xiubo Geng, Tie-Yan Liu, Tao Qin, Andrew Arnold, Hang Li, Heung-Yeung Shum |
| 2008 | SIGIR | BrowseRank: letting web users vote for page importance. | Yuting Liu, Bin Gao, Tie-Yan Liu, Ying Zhang, Zhiming Ma, Shuyuan He, Hang Li |
| 2008 | SIGIR | Directly optimizing evaluation measures in learning to rank. | Jun Xu, Tie-Yan Liu, Min Lu, Hang Li, Wei-Ying Ma |
| 2007 | CIKM | Link analysis using time series of web graphs. | Lei Yang, Lei Qi, Yan-Ping Zhao, Bin Gao, Tie-Yan Liu |
| 2007 | ECIR | Fast Large-Scale Spectral Clustering by Sequential Shrinkage Optimization. | Tie-Yan Liu, Huai-Yuan Yang, Xin Zheng, Tao Qin, Wei-Ying Ma |
| 2007 | ECIR | Untitled record | Li Zhang, Tao Qin, Tie-Yan Liu, Ying Bao, Hang Li |
| 2007 | ICML | Learning to rank: from pairwise approach to listwise approach. | Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, Hang Li |
| 2007 | WWW | Supervised rank aggregation. | Yuting Liu, Tie-Yan Liu, Tao Qin, Zhiming Ma, Hang Li |
| 2007 | SIGIR | Feature selection for ranking. | Xiubo Geng, Tie-Yan Liu, Tao Qin, Hang Li |
| 2007 | SIGIR | Ranking with multiple hyperplanes. | Tao Qin, Xu-Dong Zhang, De-Sheng Wang, Tie-Yan Liu, Wei Lai, Hang Li |
| 2007 | SIGIR | FRank: a ranking method with fidelity loss. | Ming-Feng Tsai, Tie-Yan Liu, Tao Qin, Hsin-Hsi Chen, Wei-Ying Ma |
| 2006 | ICDM | Star-Structured High-Order Heterogeneous Data Co-clustering Based on Consistent Information Theory. | Bin Gao, Tie-Yan Liu, Wei-Ying Ma |
| 2006 | ICDM | Detecting Link Spam Using Temporal Information. | Guoyang Shen, Bin Gao, Tie-Yan Liu, Guang Feng, Shiji Song, Hang Li |
| 2006 | KDD | Event detection from evolution of click-through data. | Qiankun Zhao, Tie-Yan Liu, Sourav S. Bhowmick, Wei-Ying Ma |
| 2006 | PAKDD | Level-Biased Statistics in the Hierarchical Structure of the Web. | Guang Feng, Tie-Yan Liu, Xudong Zhang, Wei-Ying Ma |
| 2006 | PAKDD | Heterogeneous Information Integration in Hierarchical Text Classification. | Huai-Yuan Yang, Tie-Yan Liu, Li Gao, Wei-Ying Ma |
| 2006 | WWW | Time-dependent semantic similarity measure of queries using historical click-through data. | Qiankun Zhao, Steven C. H. Hoi, Tie-Yan Liu, Sourav S. Bhowmick, Michael R. Lyu, Wei-Ying Ma |
| 2006 | SIGIR | Adapting ranking SVM to document retrieval. | Yunbo Cao, Jun Xu, Tie-Yan Liu, Hang Li, Yalou Huang, Hsiao-Wuen Hon |
| 2006 | SIGIR | AggregateRank: bringing order to web sites. | Guang Feng, Tie-Yan Liu, Ying Wang, Ying Bao, Zhiming Ma, Xu-Dong Zhang, Wei-Ying Ma |
| 2005 | APWEB | Level-Based Link Analysis. | Guang Feng, Tie-Yan Liu, Xu-Dong Zhang, Tao Qin, Bin Gao, Wei-Ying Ma |
| 2005 | KDD | Consistent bipartite graph co-partitioning for star-structured high-order heterogeneous data co-clustering. | Bin Gao, Tie-Yan Liu, Xin Zheng, QianSheng Cheng, Wei-Ying Ma |
| 2005 | MMM | Effective Feature Extraction for Play Detection in American Football Video. | Tie-Yan Liu, Wei-Ying Ma, HongJiang Zhang |
| 2005 | MMM | Subspace Clustering and Label Propagation for Active Feedback in Image Retrieval. | Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, Wei-Ying Ma, HongJiang Zhang |
| 2005 | WWW | Site abstraction for rare category classification in large-scale web directory. | Tie-Yan Liu, Hao Wan, Tao Qin, Zheng Chen, Yong Ren, Wei-Ying Ma |
| 2005 | WWW | An experimental study on large-scale web categorization. | Tie-Yan Liu, Yiming Yang, Hao Wan, Qian Zhou, Bin Gao, Hua-Jun Zeng, Zheng Chen, Wei-Ying Ma |
| 2005 | SIGIR | A study of relevance propagation for web search. | Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, Zheng Chen, Wei-Ying Ma |
| 2004 | ICIP | Time-constraint boost for tv commercials detection. | Tie-Yan Liu, Tao Qin, HongJiang Zhang |
| 2002 | ICIP | Constant false-alarm ratio processing for video cut detection. | Tie-Yan Liu, Xudong Zhang, Linwei Shan, Yingning Peng |
| 2001 | ISCAS | Adaptive motion tracking for fast block motion estimation. | Jian Feng, Tie-Yan Liu, Kwok-Tung Lo, Xu-Dong Zhang |