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2020 – today
- 2021
[j50]Siyuan Liu, Tong Wang
, Qijiang Xu, Bin Shao, Jian Yin, Tie-Yan Liu:
Complementing sequence-derived features with structural information extracted from fragment libraries for protein structure prediction. BMC Bioinform. 22(1): 351 (2021)- [j49]Zhumin Chen, Xueqi Cheng, Shoubin Dong, Zhicheng Dou, Jiafeng Guo, Xuanjing Huang, Yanyan Lan, Chenliang Li, Ru Li, Tie-Yan Liu, Yiqun Liu, Jun Ma, Bing Qin, Mingwen Wang, Ji-Rong Wen, Jun Xu, Min Zhang, Peng Zhang, Qi Zhang:
Information retrieval: a view from the Chinese IR community. Frontiers Comput. Sci. 15(1): 151601 (2021) - [j48]Guoqing Liu, Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Demonstration actor critic. Neurocomputing 434: 194-202 (2021) - [j47]Zhibing Zhao, Yingce Xia, Tao Qin, Lirong Xia, Tie-Yan Liu:
Dual Learning: Theoretical Study and an Algorithmic Extension. SN Comput. Sci. 2(5): 413 (2021) - [c236]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 - [c235]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
How Does Data Augmentation Affect Privacy in Machine Learning? AAAI 2021: 10746-10753 - [c234]Chen Zhang, Xu Tan, Yi Ren, Tao Qin, Kejun Zhang, Tie-Yan Liu:
UWSpeech: Speech to Speech Translation for Unwritten Languages. AAAI 2021: 14319-14327 - [c233]Lanqing Xue, Kaitao Song, Duocai Wu, Xu Tan, Nevin L. Zhang, Tao Qin, Wei-Qiang Zhang, Tie-Yan Liu:
DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modeling. ACL/IJCNLP (1) 2021: 69-81 - [c232]Mingliang Zeng, Xu Tan, Rui Wang, Zeqian Ju, Tao Qin, Tie-Yan Liu:
MusicBERT: Symbolic Music Understanding with Large-Scale Pre-Training. ACL/IJCNLP (Findings) 2021: 791-800 - [c231]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 - [c230]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 - [c229]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 - [c228]Shuqi Lu, Di He, Chenyan Xiong, Guolin Ke, Waleed Malik, Zhicheng Dou, Paul Bennett, Tie-Yan Liu, Arnold Overwijk:
Less is More: Pretrain a Strong Siamese Encoder for Dense Text Retrieval Using a Weak Decoder. EMNLP (1) 2021: 2780-2791 - [c227]Yichong Leng, Xu Tan, Rui Wang, Linchen Zhu, Jin Xu, Wenjie Liu, Linquan Liu, Xiang-Yang Li, Tao Qin, Edward Lin, Tie-Yan Liu:
FastCorrect 2: Fast Error Correction on Multiple Candidates for Automatic Speech Recognition. EMNLP (Findings) 2021: 4328-4337 - [c226]Renqian Luo, Xu Tan, Rui Wang, Tao Qin, Jinzhu Li, Sheng Zhao, Enhong Chen, Tie-Yan Liu:
Lightspeech: Lightweight and Fast Text to Speech with Neural Architecture Search. ICASSP 2021: 5699-5703 - [c225]Yuzi Yan, Xu Tan, Bohan Li, Tao Qin, Sheng Zhao, Yuan Shen, Tie-Yan Liu:
Adaspeech 2: Adaptive Text to Speech with Untranscribed Data. ICASSP 2021: 6613-6617 - [c224]Chen Zhang, Yi Ren, Xu Tan, Jinglin Liu, Kejun Zhang, Tao Qin, Sheng Zhao, Tie-Yan Liu:
Denoispeech: Denoising Text to Speech with Frame-Level Noise Modeling. ICASSP 2021: 7063-7067 - [c223]Qiyu Wu, Chen Xing, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu:
Taking Notes on the Fly Helps Language Pre-Training. ICLR 2021 - [c222]Yi Ren, Chenxu Hu, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, Tie-Yan Liu:
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech. ICLR 2021 - [c221]Mingjian Chen, Xu Tan, Bohan Li, Yanqing Liu, Tao Qin, Sheng Zhao, Tie-Yan Liu:
AdaSpeech: Adaptive Text to Speech for Custom Voice. ICLR 2021 - [c220]Guolin Ke, Di He, Tie-Yan Liu:
Rethinking Positional Encoding in Language Pre-training. ICLR 2021 - [c219]Guoqing Liu, Chuheng Zhang, Li Zhao, Tao Qin, Jinhua Zhu, Jian Li, Nenghai Yu, Tie-Yan Liu:
Return-Based Contrastive Representation Learning for Reinforcement Learning. ICLR 2021 - [c218]Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu:
Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning. ICLR 2021 - [c217]Jinhua Zhu, Lijun Wu, Yingce Xia, Shufang Xie, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu:
IOT: Instance-wise Layer Reordering for Transformer Structures. ICLR 2021 - [c216]Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang:
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training. ICML 2021: 1204-1215 - [c215]Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu:
How could Neural Networks understand Programs? ICML 2021: 8476-8486 - [c214]Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu:
The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks. ICML 2021: 10849-10858 - [c213]Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie, Tao Qin, Tie-Yan Liu:
Temporally Correlated Task Scheduling for Sequence Learning. ICML 2021: 11274-11284 - [c212]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
Large Scale Private Learning via Low-rank Reparametrization. ICML 2021: 12208-12218 - [c211]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 - [c210]Pushi Zhang, Li Zhao, Guoqing Liu, Jiang Bian, Minlie Huang, Tao Qin, Tie-Yan Liu:
Independence-aware Advantage Estimation. IJCAI 2021: 3349-3355 - [c209]Rui Wang, Xu Tan, Renqian Luo, Tao Qin, Tie-Yan Liu:
A Survey on Low-Resource Neural Machine Translation. IJCAI 2021: 4636-4643 - [c208]Jin Xu, Xu Tan, Renqian Luo, Kaitao Song, Jian Li, Tao Qin, Tie-Yan Liu:
NAS-BERT: Task-Agnostic and Adaptive-Size BERT Compression with Neural Architecture Search. KDD 2021: 1933-1943 - [c207]Zhen Wu, Lijun Wu, Qi Meng, Yingce Xia, Shufang Xie, Tao Qin, Xinyu Dai, Tie-Yan Liu:
UniDrop: A Simple yet Effective Technique to Improve Transformer without Extra Cost. NAACL-HLT 2021: 3865-3878 - [c206]Xufang Luo, Qi Meng, Wei Chen, Yunhong Wang, Tie-Yan Liu:
Path-BN: Towards effective batch normalization in the Path Space for ReLU networks. UAI 2021: 834-843 - [c205]Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu:
REST: Relational Event-driven Stock Trend Forecasting. WWW 2021: 1-10 - [i175]Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu:
BN-invariant sharpness regularizes the training model to better generalization. CoRR abs/2101.02944 (2021) - [i174]Renqian Luo, Xu Tan, Rui Wang, Tao Qin, Jinzhu Li, Sheng Zhao, Enhong Chen, Tie-Yan Liu:
LightSpeech: Lightweight and Fast Text to Speech with Neural Architecture Search. CoRR abs/2102.04040 (2021) - [i173]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) - [i172]Shengjie Luo, Kaiyuan Gao, Shuxin Zheng, Guolin Ke, Di He, Liwei Wang, Tie-Yan Liu:
Revisiting Language Encoding in Learning Multilingual Representations. CoRR abs/2102.08357 (2021) - [i171]Shuqi Lu, Chenyan Xiong, Di He, Guolin Ke, Waleed Malik, Zhicheng Dou, Paul Bennett, Tie-Yan Liu, Arnold Overwijk:
Less is More: Pre-training a Strong Siamese Encoder Using a Weak Decoder. CoRR abs/2102.09206 (2021) - [i170]Guoqing Liu, Chuheng Zhang, Li Zhao, Tao Qin, Jinhua Zhu, Jian Li, Nenghai Yu, Tie-Yan Liu:
Return-Based Contrastive Representation Learning for Reinforcement Learning. CoRR abs/2102.10960 (2021) - [i169]Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu:
Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning. CoRR abs/2102.12677 (2021) - [i168]Chengxuan Ying, Guolin Ke, Di He, Tie-Yan Liu:
LazyFormer: Self Attention with Lazy Update. CoRR abs/2102.12702 (2021) - [i167]Mingjian Chen, Xu Tan, Bohan Li, Yanqing Liu, Tao Qin, Sheng Zhao, Tie-Yan Liu:
AdaSpeech: Adaptive Text to Speech for Custom Voice. CoRR abs/2103.00993 (2021) - [i166]Jinhua Zhu, Lijun Wu, Yingce Xia, Shufang Xie, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu:
IOT: Instance-wise Layer Reordering for Transformer Structures. CoRR abs/2103.03457 (2021) - [i165]Jindong Wang, Wenjie Feng, Chang Liu, Chaohui Yu, Mingxuan Du, Renjun Xu, Tao Qin, Tie-Yan Liu:
Learning Invariant Representations across Domains and Tasks. CoRR abs/2103.05114 (2021) - [i164]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) - [i163]Zhen Wu, Lijun Wu, Qi Meng, Yingce Xia, Shufang Xie, Tao Qin, Xinyu Dai, Tie-Yan Liu:
UniDrop: A Simple yet Effective Technique to Improve Transformer without Extra Cost. CoRR abs/2104.04946 (2021) - [i162]Yuzi Yan, Xu Tan, Bohan Li, Tao Qin, Sheng Zhao, Yuan Shen, Tie-Yan Liu:
AdaSpeech 2: Adaptive Text to Speech with Untranscribed Data. CoRR abs/2104.09715 (2021) - [i161]Yichong Leng, Xu Tan, Linchen Zhu, Jin Xu, Renqian Luo, Linquan Liu, Tao Qin, Xiang-Yang Li, Ed Lin, Tie-Yan Liu:
FastCorrect: Fast Error Correction with Edit Alignment for Automatic Speech Recognition. CoRR abs/2105.03842 (2021) - [i160]Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu:
How could Neural Networks understand Programs? CoRR abs/2105.04297 (2021) - [i159]Jinhui Yuan, Fei Pan, Chunting Zhou, Tao Qin, Tie-Yan Liu:
Learning Structures for Deep Neural Networks. CoRR abs/2105.13905 (2021) - [i158]Jin Xu, Xu Tan, Renqian Luo, Kaitao Song, Jian Li, Tao Qin, Tie-Yan Liu:
NAS-BERT: Task-Agnostic and Adaptive-Size BERT Compression with Neural Architecture Search. CoRR abs/2105.14444 (2021) - [i157]Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu:
Adversarial Training with Rectified Rejection. CoRR abs/2105.14785 (2021) - [i156]Ziming Liu, Bohan Wang, Qi Meng, Wei Chen, Max Tegmark, Tie-Yan Liu:
Machine-Learning Non-Conservative Dynamics for New-Physics Detection. CoRR abs/2106.00026 (2021) - [i155]Shiqi Gong, Qi Meng, Yue Wang, Lijun Wu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu:
Incorporating NODE with Pre-trained Neural Differential Operator for Learning Dynamics. CoRR abs/2106.04166 (2021) - [i154]Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu:
Do Transformers Really Perform Bad for Graph Representation? CoRR abs/2106.05234 (2021) - [i153]Mingliang Zeng, Xu Tan, Rui Wang, Zeqian Ju, Tao Qin, Tie-Yan Liu:
MusicBERT: Symbolic Music Understanding with Large-Scale Pre-Training. CoRR abs/2106.05630 (2021) - [i152]Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu:
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Driven Adaptive Prior. CoRR abs/2106.06406 (2021) - [i151]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
Large Scale Private Learning via Low-rank Reparametrization. CoRR abs/2106.09352 (2021) - [i150]Jinhua Zhu, Yingce Xia, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu:
Dual-view Molecule Pre-training. CoRR abs/2106.10234 (2021) - [i149]Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu:
Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding. CoRR abs/2106.12566 (2021) - [i148]Xiaobo Liang, Lijun Wu, Juntao Li, Yue Wang, Qi Meng, Tao Qin, Wei Chen, Min Zhang, Tie-Yan Liu:
R-Drop: Regularized Dropout for Neural Networks. CoRR abs/2106.14448 (2021) - [i147]Yichi Zhou, Shihong Song, Huishuai Zhang, Jun Zhu, Wei Chen, Tie-Yan Liu:
Regularized OFU: an Efficient UCB Estimator forNon-linear Contextual Bandit. CoRR abs/2106.15128 (2021) - [i146]Xu Tan, Tao Qin, Frank K. Soong, Tie-Yan Liu:
A Survey on Neural Speech Synthesis. CoRR abs/2106.15561 (2021) - [i145]Chang Liu, Haoyue Tang, Tao Qin, Jintao Wang, Tie-Yan Liu:
On the Generative Utility of Cyclic Conditionals. CoRR abs/2106.15962 (2021) - [i144]Yue Jin, Yue Zhang, Tao Qin, Xudong Zhang, Jian Yuan, Houqiang Li, Tie-Yan Liu:
Supervised Off-Policy Ranking. CoRR abs/2107.01360 (2021) - [i143]Lanqing Xue, Kaitao Song, Duocai Wu, Xu Tan, Nevin L. Zhang, Tao Qin, Wei-Qiang Zhang, Tie-Yan Liu:
DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modeling. CoRR abs/2107.01875 (2021) - [i142]Xiangyu Zheng, Xinwei Sun, Wei Chen, Tie-Yan Liu:
Causally Invariant Predictor with Shift-Robustness. CoRR abs/2107.01876 (2021) - [i141]Yuzi Yan, Xu Tan, Bohan Li, Guangyan Zhang, Tao Qin, Sheng Zhao, Yuan Shen, Wei-Qiang Zhang, Tie-Yan Liu:
AdaSpeech 3: Adaptive Text to Speech for Spontaneous Style. CoRR abs/2107.02530 (2021) - [i140]Rui Wang, Xu Tan, Renqian Luo, Tao Qin, Tie-Yan Liu:
A Survey on Low-Resource Neural Machine Translation. CoRR abs/2107.04239 (2021) - [i139]Jin Xu, Xu Tan, Kaitao Song, Renqian Luo, Yichong Leng, Tao Qin, Tie-Yan Liu, Jian Li:
Analyzing and Mitigating Interference in Neural Architecture Search. CoRR abs/2108.12821 (2021) - [i138]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) - [i137]Zeqian Ju, Peiling Lu, Xu Tan, Rui Wang, Chen Zhang, Songruoyao Wu, Kejun Zhang, Xiangyang Li, Tao Qin, Tie-Yan Liu:
TeleMelody: Lyric-to-Melody Generation with a Template-Based Two-Stage Method. CoRR abs/2109.09617 (2021) - [i136]Yutai Hou, Yingce Xia, Lijun Wu, Shufang Xie, Yang Fan, Jinhua Zhu, Wanxiang Che, Tao Qin, Tie-Yan Liu:
Discovering Drug-Target Interaction Knowledge from Biomedical Literature. CoRR abs/2109.13187 (2021) - [i135]Yichong Leng, Xu Tan, Rui Wang, Linchen Zhu, Jin Xu, Linquan Liu, Tao Qin, Xiang-Yang Li, Edward Lin, Tie-Yan Liu:
FastCorrect 2: Fast Error Correction on Multiple Candidates for Automatic Speech Recognition. CoRR abs/2109.14420 (2021) - [i134]Siyuan Liu, Yusong Wang, Tong Wang, Yifan Deng, Liang He, Bin Shao, Jian Yin, Nanning Zheng, Tie-Yan Liu:
Improved Drug-target Interaction Prediction with Intermolecular Graph Transformer. CoRR abs/2110.07347 (2021) - [i133]Pushi Zhang, Xiaoyu Chen, Li Zhao, Wei Xiong, Tao Qin, Tie-Yan Liu:
Distributional Reinforcement Learning for Multi-Dimensional Reward Functions. CoRR abs/2110.13578 (2021) - [i132]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) - [i131]Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu:
Optimizing Information-theoretical Generalization Bounds via Anisotropic Noise in SGLD. CoRR abs/2110.13750 (2021) - [i130]Jongjin Park, Younggyo Seo, Chang Liu, Li Zhao, Tao Qin, Jinwoo Shin, Tie-Yan Liu:
Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning. CoRR abs/2110.14118 (2021) - [i129]Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Bin Shao, Tie-Yan Liu:
Equivariant vector field network for many-body system modeling. CoRR abs/2110.14811 (2021) - [i128]Liang He, Shizhuo Zhang, Lijun Wu, Huanhuan Xia, Fusong Ju, He Zhang, Siyuan Liu, Yingce Xia, Jianwei Zhu, Pan Deng, Bin Shao, Tao Qin, Tie-Yan Liu:
Pre-training Co-evolutionary Protein Representation via A Pairwise Masked Language Model. CoRR abs/2110.15527 (2021) - [i127]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
Indiscriminate Poisoning Attacks Are Shortcuts. CoRR abs/2111.00898 (2021) - [i126]Minghuan Liu, Hanye Zhao, Zhengyu Yang, Jian Shen, Weinan Zhang, Li Zhao, Tie-Yan Liu:
Curriculum Offline Imitation Learning. CoRR abs/2111.02056 (2021) - [i125]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) - [i124]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
- [j46]Yue Wang, Yuting Liu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu:
Target transfer Q-learning and its convergence analysis. Neurocomputing 392: 11-22 (2020) - [j45]Yang Fan, Fei Tian, Yingce Xia, Tao Qin, Xiang-Yang Li, Tie-Yan Liu:
Searching Better Architectures for Neural Machine Translation. IEEE ACM Trans. Audio Speech Lang. Process. 28: 1574-1585 (2020) - [j44]Wenzheng Hu, Junqi Jin, Tie-Yan Liu, Changshui Zhang:
Automatically Design Convolutional Neural Networks by Optimization With Submodularity and Supermodularity. IEEE Trans. Neural Networks Learn. Syst. 31(9): 3215-3229 (2020) - [j43]Shicong Cen, Huishuai Zhang, Yuejie Chi, Wei Chen, Tie-Yan Liu:
Convergence of Distributed Stochastic Variance Reduced Methods Without Sampling Extra Data. IEEE Trans. Signal Process. 68: 3976-3989 (2020) - [c204]Yiren Wang, Lijun Wu, Yingce Xia, Tao Qin, ChengXiang Zhai, Tie-Yan Liu:
Transductive Ensemble Learning for Neural Machine Translation. AAAI 2020: 6291-6298 - [c203]Zhenhui Xu, Guolin Ke, Jia Zhang, Jiang Bian, Tie-Yan Liu:
Light Multi-Segment Activation for Model Compression. AAAI 2020: 6542-6549 - [c202]Junliang Guo, Xu Tan, Linli Xu, Tao Qin, Enhong Chen, Tie-Yan Liu:
Fine-Tuning by Curriculum Learning for Non-Autoregressive Neural Machine Translation. AAAI 2020: 7839-7846 - [c201]Yi Ren, Jinglin Liu, Xu Tan, Zhou Zhao, Sheng Zhao, Tie-Yan Liu:
A Study of Non-autoregressive Model for Sequence Generation. ACL 2020: 149-159 - [c200]Yi Ren, Jinglin Liu, Xu Tan, Chen Zhang, Tao Qin, Zhou Zhao, Tie-Yan Liu:
SimulSpeech: End-to-End Simultaneous Speech to Text Translation. ACL 2020: 3787-3796 - [c199]Wentao Xu, Shun Zheng, Liang He, Bin Shao, Jian Yin, Tie-Yan Liu:
SEEK: Segmented Embedding of Knowledge Graphs. ACL 2020: 3888-3897 - [c198]Zhibing Zhao, Yingce Xia, Tao Qin, Lirong Xia, Tie-Yan Liu:
Dual Learning: Theoretical Study and an Algorithmic Extension. ACML 2020: 321-336 - [c197]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 - [c196]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 - [c195]Jinhua Zhu, Yingce Xia, Lijun Wu, Di He, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu:
Incorporating BERT into Neural Machine Translation. ICLR 2020 - [c194]Lijun Wu, Shufang Xie, Yingce Xia, Yang Fan, Jian-Huang Lai, Tao Qin, Tie-Yan Liu:
Sequence Generation with Mixed Representations. ICML 2020: 10388-10398 - [c193]Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tie-Yan Liu:
On Layer Normalization in the Transformer Architecture. ICML 2020: 10524-10533 - [c192]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
Gradient Perturbation is Underrated for Differentially Private Convex Optimization. IJCAI 2020: 3117-3123 - [c191]Jinglin Liu, Yi Ren, Xu Tan, Chen Zhang, Tao Qin, Zhou Zhao, Tie-Yan Liu:
Task-Level Curriculum Learning for Non-Autoregressive Neural Machine Translation. IJCAI 2020: 3861-3867 - [c190]Yi Ren, Xu Tan, Tao Qin, Jian Luan, Zhou Zhao, Tie-Yan Liu:
DeepSinger: Singing Voice Synthesis with Data Mined From the Web. KDD 2020: 1979-1989 - [c189]Jin Xu, Xu Tan, Yi Ren, Tao Qin, Jian Li, Sheng Zhao, Tie-Yan Liu:
LRSpeech: Extremely Low-Resource Speech Synthesis and Recognition. KDD 2020: 2802-2812 - [c188]Yi Ren, Jinzheng He, Xu Tan, Tao Qin, Zhou Zhao, Tie-Yan Liu:
PopMAG: Pop Music Accompaniment Generation. ACM Multimedia 2020: 1198-1206 - [c187]Weicong Chen, Xu Tan, Yingce Xia, Tao Qin, Yu Wang, Tie-Yan Liu:
DualLip: A System for Joint Lip Reading and Generation. ACM Multimedia 2020: 1985-1993 - [c186]Zichuan Lin, Derek Yang, Li Zhao, Tao Qin, Guangwen Yang, Tie-Yan Liu:
RD$^2$: Reward Decomposition with Representation Decomposition. NeurIPS 2020 - [c185]Renqian Luo, Xu Tan, Rui Wang, Tao Qin, Enhong Chen, Tie-Yan Liu:
Semi-Supervised Neural Architecture Search. NeurIPS 2020 - [c184]Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, Tie-Yan Liu:
MPNet: Masked and Permuted Pre-training for Language Understanding. NeurIPS 2020 - [e8]Yennun Huang, Irwin King, Tie-Yan Liu, Maarten van Steen:
WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020. ACM / IW3C2 2020, ISBN 978-1-4503-7023-3 [contents] - [e7]Amal El Fallah Seghrouchni, Gita Sukthankar, Tie-Yan Liu, Maarten van Steen:
Companion of The 2020 Web Conference 2020, Taipei, Taiwan, April 20-24, 2020. ACM / IW3C2 2020, ISBN 978-1-4503-7024-0 [contents] - [i123]Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tie-Yan Liu:
On Layer Normalization in the Transformer Architecture. CoRR abs/2002.04745 (2020) - [i122]Jinhua Zhu, Yingce Xia, Lijun Wu, Di He, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu:
Incorporating BERT into Neural Machine Translation. CoRR abs/2002.06823 (2020) - [i121]Renqian Luo, Xu Tan, Rui Wang, Tao Qin, Enhong Chen, Tie-Yan Liu:
Semi-Supervised Neural Architecture Search. CoRR abs/2002.10389 (2020) - [i120]Junjie Li, Sotetsu Koyamada, Qiwei Ye, Guoqing Liu, Chao Wang, Ruihan Yang, Li Zhao, Tao Qin, Tie-Yan Liu, Hsiao-Wuen Hon:
Suphx: Mastering Mahjong with Deep Reinforcement Learning. CoRR abs/2003.13590 (2020) - [i119]Yuxuan Song, Qiwei Ye, Minkai Xu, Tie-Yan Liu:
Discriminator Contrastive Divergence: Semi-Amortized Generative Modeling by Exploring Energy of the Discriminator. CoRR abs/2004.01704 (2020) - [i118]Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, Tie-Yan Liu:
MPNet: Masked and Permuted Pre-training for Language Understanding. CoRR abs/2004.09297 (2020) - [i117]Yi Ren, Jinglin Liu, Xu Tan, Sheng Zhao, Zhou Zhao, Tie-Yan Liu:
A Study of Non-autoregressive Model for Sequence Generation. CoRR abs/2004.10454 (2020) - [i116]Kaitao Song, Hao Sun, Xu Tan, Tao Qin, Jianfeng Lu, Hongzhi Liu, Tie-Yan Liu:
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