Timezone: »
Author Information
Da Yu (Sun Yat-sen University)
Huishuai Zhang (Microsoft)
Wei Chen (Microsoft Research)
Jian Yin (Sun Yat-Sen University)
Tie-Yan Liu (Microsoft Research Asia)
Tie-Yan Liu is a principal researcher of Microsoft Research Asia, leading the research on artificial intelligence and machine learning. He is very well known for his pioneer work on learning to rank and computational advertising, and his recent research interests include deep learning, reinforcement learning, and distributed machine learning. Many of his technologies have been transferred to Microsoft’s products and online services (such as Bing, Microsoft Advertising, and Azure), and open-sourced through Microsoft Cognitive Toolkit (CNTK), Microsoft Distributed Machine Learning Toolkit (DMTK), and Microsoft Graph Engine. On the other hand, he has been actively contributing to academic communities. He is an adjunct/honorary professor at Carnegie Mellon University (CMU), University of Nottingham, and several other universities in China. His papers have been cited for tens of thousands of times in refereed conferences and journals. He has won quite a few awards, including the best student paper award at SIGIR (2008), the most cited paper award at Journal of Visual Communications and Image Representation (2004-2006), the research break-through award (2012) and research-team-of-the-year award (2017) at Microsoft Research, and Top-10 Springer Computer Science books by Chinese authors (2015), and the most cited Chinese researcher by Elsevier (2017). He has been invited to serve as general chair, program committee chair, local chair, or area chair for a dozen of top conferences including SIGIR, WWW, KDD, ICML, NIPS, IJCAI, AAAI, ACL, ICTIR, as well as associate editor of ACM Transactions on Information Systems, ACM Transactions on the Web, and Neurocomputing. Tie-Yan Liu is a fellow of the IEEE, a distinguished member of the ACM, and a vice chair of the CIPS information retrieval technical committee.
Related Events (a corresponding poster, oral, or spotlight)
-
2021 Spotlight: Large Scale Private Learning via Low-rank Reparametrization »
Fri. Jul 23rd 01:20 -- 01:25 AM Room
More from the Same Authors
-
2022 Poster: Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum »
Zeke Xie · Xinrui Wang · Huishuai Zhang · Issei Sato · Masashi Sugiyama -
2022 Poster: 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 Spotlight: 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 Oral: Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum »
Zeke Xie · Xinrui Wang · Huishuai Zhang · Issei Sato · Masashi Sugiyama -
2022 Poster: 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 Poster: Supervised Off-Policy Ranking »
Yue Jin · Yue Zhang · Tao Qin · Xudong Zhang · Jian Yuan · Houqiang Li · Tie-Yan Liu -
2022 Spotlight: Supervised Off-Policy Ranking »
Yue Jin · Yue Zhang · Tao Qin · Xudong Zhang · Jian Yuan · Houqiang Li · Tie-Yan Liu -
2022 Spotlight: 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 -
2021 Poster: The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks »
Bohan Wang · Qi Meng · Wei Chen · Tie-Yan Liu -
2021 Oral: The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks »
Bohan Wang · Qi Meng · Wei Chen · Tie-Yan Liu -
2021 Poster: 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 Poster: GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training »
Tianle Cai · Shengjie Luo · Keyulu Xu · Di He · Tie-Yan Liu · Liwei Wang -
2021 Spotlight: GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training »
Tianle Cai · Shengjie Luo · Keyulu Xu · Di He · Tie-Yan Liu · Liwei Wang -
2021 Spotlight: 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 Tutorial: Privacy in learning: Basics and the interplay »
Huishuai Zhang · Wei Chen -
2021 : Privacy in learning: Basics and the interplay »
Huishuai Zhang · Wei Chen -
2020 Poster: 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 Poster: Sequence Generation with Mixed Representations »
Lijun Wu · Shufang Xie · Yingce Xia · Yang Fan · Jian-Huang Lai · Tao Qin · Tie-Yan Liu -
2019 Poster: Efficient Training of BERT by Progressively Stacking »
Linyuan Gong · Di He · Zhuohan Li · Tao Qin · Liwei Wang · Tie-Yan Liu -
2019 Oral: Efficient Training of BERT by Progressively Stacking »
Linyuan Gong · Di He · Zhuohan Li · Tao Qin · Liwei Wang · Tie-Yan Liu -
2018 Poster: Towards Binary-Valued Gates for Robust LSTM Training »
Zhuohan Li · Di He · Fei Tian · Wei Chen · Tao Qin · Liwei Wang · Tie-Yan Liu -
2018 Oral: Towards Binary-Valued Gates for Robust LSTM Training »
Zhuohan Li · Di He · Fei Tian · Wei Chen · Tao Qin · Liwei Wang · Tie-Yan Liu -
2017 Poster: Asynchronous Stochastic Gradient Descent with Delay Compensation »
Shuxin Zheng · Qi Meng · Taifeng Wang · Wei Chen · Nenghai Yu · Zhiming Ma · Tie-Yan Liu -
2017 Talk: Asynchronous Stochastic Gradient Descent with Delay Compensation »
Shuxin Zheng · Qi Meng · Taifeng Wang · Wei Chen · Nenghai Yu · Zhiming Ma · Tie-Yan Liu -
2017 Poster: Dual Supervised Learning »
Yingce Xia · Tao Qin · Wei Chen · Jiang Bian · Nenghai Yu · Tie-Yan Liu -
2017 Talk: Dual Supervised Learning »
Yingce Xia · Tao Qin · Wei Chen · Jiang Bian · Nenghai Yu · Tie-Yan Liu