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ORCIDLiwei Wang 0001
王立威
Person information
- unicode name: 王立威
- affiliation: Peking University, Department of Machine Intelligence, Beijing, China
- not to be confused with: Liwei Wang 0009
Other persons with the same name
- Liwei Wang (aka: Li-wei Wang, Li-Wei Wang) — disambiguation page
- Liwei Wang 0002
![[0000-0003-1076-5827]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0003-1076-5827")
— University of British Columbia, School of Engineering, Okanagan, BC, Canada (and 1 more) - Liwei Wang 0003 — Electronics Research Institute of the Ministry of Industry and Information Technology, Guangzhou, China
- Liwei Wang 0004 — University of Birmingham, UK
- Liwei Wang 0005 — Beijing University of Posts and Telecommunications, China
- Liwei Wang 0006 — Jiangsu University of Science and Technology, China
- Liwei Wang 0007 — Harbin Engineering University, China
- Liwei Wang 0008 — Pharmaceutical Product Development Inc, Morrisville, NC, USA
- Liwei Wang 0009 — Chinese University of Hong Kong (CUHK), Hong Kong (and 2 more)
- Liwei Wang 0010 — Mayo Clinic, Rochester, MN, USA (and 1 more)
- Liwei Wang 0011 — Wuhan University, China
- Li-Wei Wang 0013 (aka: Liwei Wang 0013) — National Tsing Hua University, Hsinchu City, Taiwan
- Liwei Wang 0014 — Beijing Jiaotong University, School of Traffic and Transportation, China
- Liwei Wang 0015 — Wuhan University, International School of Software, China
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Journal Articles
- 2020
[j27]Aoxue Li, Zhiwu Lu, Jiechao Guan, Tao Xiang, Liwei Wang, Ji-Rong Wen:
Transferrable Feature and Projection Learning with Class Hierarchy for Zero-Shot Learning. Int. J. Comput. Vis. 128(12): 2810-2827 (2020)- 2018
- [j26]Aoxue Li, Zhiwu Lu, Liwei Wang, Peng Han, Ji-Rong Wen:
Large-Scale Sparse Learning From Noisy Tags for Semantic Segmentation. IEEE Trans. Cybern. 48(1): 253-263 (2018) - 2017
- [j25]Zhiwu Lu, Zhenyong Fu, Tao Xiang, Peng Han, Liwei Wang, Xin Gao:
Learning from Weak and Noisy Labels for Semantic Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 39(3): 486-500 (2017) - [j24]Aoxue Li, Zhiwu Lu, Liwei Wang, Tao Xiang, Ji-Rong Wen:
Zero-Shot Scene Classification for High Spatial Resolution Remote Sensing Images. IEEE Trans. Geosci. Remote. Sens. 55(7): 4157-4167 (2017) - 2016
- [j23]Zhiwu Lu, Liwei Wang, Ji-Rong Wen:
Image classification by visual bag-of-words refinement and reduction. Neurocomputing 173: 373-384 (2016) - [j22]Li Tong, Yao Liu, Bo Wang, Liwei Wang, Hongbin Zha:
Nonlinear Dimensionality Reduction by Local Orthogonality Preserving Alignment. J. Comput. Sci. Technol. 31(3): 512-524 (2016) - [j21]Ziteng Wang, Chi Jin, Kai Fan, Jiaqi Zhang, Junliang Huang, Yiqiao Zhong, Liwei Wang:
Differentially Private Data Releasing for Smooth Queries. J. Mach. Learn. Res. 17: 51:1-51:42 (2016) - [j20]Wayne Xin Zhao, Sui Li, Yulan He, Liwei Wang, Ji-Rong Wen, Xiaoming Li:
Exploring demographic information in social media for product recommendation. Knowl. Inf. Syst. 49(1): 61-89 (2016) - 2015
- [j19]Liwei Wang, Jiapeng Zhang:
On the measurement complexity of differentially private query answering. Sci. China Inf. Sci. 58(9): 1-11 (2015) - [j18]Zhiwu Lu, Liwei Wang:
Learning descriptive visual representation for image classification and annotation. Pattern Recognit. 48(2): 498-508 (2015) - [j17]Zhiwu Lu, Liwei Wang:
Noise-robust semi-supervised learning via fast sparse coding. Pattern Recognit. 48(2): 605-612 (2015) - [j16]Zhiwu Lu, Peng Han, Liwei Wang, Ji-Rong Wen:
Semantic Sparse Recoding of Visual Content for Image Applications. IEEE Trans. Image Process. 24(1): 176-188 (2015) - 2014
- [j15]Kai Fan, Hongyi Zhang, Songbai Yan, Liwei Wang, Wensheng Zhang, Jufu Feng:
Learning a generative classifier from label proportions. Neurocomputing 139: 47-55 (2014) - 2013
- [j14]Di He, Wei Chen, Liwei Wang, Tie-Yan Liu:
Online learning for auction mechanism in bandit setting. Decis. Support Syst. 56: 379-386 (2013) - 2012
- [j13]Liwei Wang, Xiaocheng Deng, Zhaoxiang Jing, Jufu Feng:
Further results on the margin explanation of boosting: new algorithm and experiments. Sci. China Inf. Sci. 55(7): 1551-1562 (2012) - 2011
- [j12]Liwei Wang, Masashi Sugiyama, Zhaoxiang Jing, Cheng Yang, Zhi-Hua Zhou, Jufu Feng:
A Refined Margin Analysis for Boosting Algorithms via Equilibrium Margin. J. Mach. Learn. Res. 12: 1835-1863 (2011) - 2009
- [j11]Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Shohei Hido, Jun Sese, Ichiro Takeuchi, Liwei Wang:
A Density-ratio Framework for Statistical Data Processing. IPSJ Trans. Comput. Vis. Appl. 1: 183-208 (2009) - [j10]Liwei Wang, Masashi Sugiyama, Cheng Yang, Kohei Hatano, Jufu Feng:
Theory and Algorithm for Learning with Dissimilarity Functions. Neural Comput. 21(5): 1459-1484 (2009) - [j9]Cheng Yang, Liwei Wang, Jufu Feng:
A Novel Margin Based Algorithm for Feature Extraction. New Gener. Comput. 27(4): 285-305 (2009) - 2008
- [j8]Cheng Yang, Liwei Wang, Jufu Feng:
On Feature Extraction via Kernels. IEEE Trans. Syst. Man Cybern. Part B 38(2): 553-557 (2008) - 2007
- [j7]Xichen Sun, Liwei Wang, Jufu Feng:
Further results on the subspace distance. Pattern Recognit. 40(1): 328-329 (2007) - 2006
- [j6]Liwei Wang, Jufu Feng:
Comments on "Fundamental Limits of Reconstruction-Based Superresolution Algorithms under Local Translation'. IEEE Trans. Pattern Anal. Mach. Intell. 28(5): 846 (2006) - [j5]Liwei Wang, Xiao Wang, Jufu Feng:
Subspace distance analysis with application to adaptive Bayesian algorithm for face recognition. Pattern Recognit. 39(3): 456-464 (2006) - [j4]Liwei Wang, Xiao Wang, Jufu Feng:
On image matrix based feature extraction algorithms. IEEE Trans. Syst. Man Cybern. Part B 36(1): 194-197 (2006) - 2005
- [j3]Liwei Wang, Yan Zhang, Jufu Feng:
On the Euclidean Distance of Images. IEEE Trans. Pattern Anal. Mach. Intell. 27(8): 1334-1339 (2005) - [j2]Liwei Wang, Xiao Wang, Jufu Feng:
Intrapersonal subspace analysis with application to adaptive Bayesian face recognition. Pattern Recognit. 38(4): 617-621 (2005) - [j1]Liwei Wang, Xiao Wang, Xuerong Zhang, Jufu Feng:
The equivalence of two-dimensional PCA to line-based PCA. Pattern Recognit. Lett. 26(1): 57-60 (2005)
Conference and Workshop Papers
- 2023
- [c102]Di He, Shanda Li, Wenlei Shi, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu:
Learning Physics-Informed Neural Networks without Stacked Back-propagation. AISTATS 2023: 3034-3047 - [c101]Haiyang Wang, Chen Shi, Shaoshuai Shi, Meng Lei, Sen Wang, Di He, Bernt Schiele, Liwei Wang:
DSVT: Dynamic Sparse Voxel Transformer with Rotated Sets. CVPR 2023: 13520-13529 - [c100]Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Liwei Wang, Tong Zhang:
Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game. ICLR 2023 - [c99]Jiachen Hu, Han Zhong, Chi Jin, Liwei Wang:
Provable Sim-to-real Transfer in Continuous Domain with Partial Observations. ICLR 2023 - [c98]Shengjie Luo, Tianlang Chen, Yixian Xu, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He:
One Transformer Can Understand Both 2D & 3D Molecular Data. ICLR 2023 - [c97]Quanlin Wu, Hang Ye, Yuntian Gu, Huishuai Zhang, Liwei Wang, Di He:
Denoising Masked Autoencoders Help Robust Classification. ICLR 2023 - [c96]Bohang Zhang, Shengjie Luo, Liwei Wang, Di He:
Rethinking the Expressive Power of GNNs via Graph Biconnectivity. ICLR 2023 - [c95]Haotian Ye, Xiaoyu Chen, Liwei Wang, Simon Shaolei Du:
On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness. ICML 2023: 39770-39800 - [c94]Bohang Zhang, Guhao Feng, Yiheng Du, Di He, Liwei Wang:
A Complete Expressiveness Hierarchy for Subgraph GNNs via Subgraph Weisfeiler-Lehman Tests. ICML 2023: 41019-41077 - [c93]Guhao Feng, Bohang Zhang, Yuntian Gu, Haotian Ye, Di He, Liwei Wang:
Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective. NeurIPS 2023 - [c92]Jiayi Huang, Han Zhong, Liwei Wang, Lin Yang:
Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds. NeurIPS 2023 - [c91]Yunchang Yang, Han Zhong, Tianhao Wu, Bin Liu, Liwei Wang, Simon S. Du:
A Reduction-based Framework for Sequential Decision Making with Delayed Feedback. NeurIPS 2023 - 2022
- [c90]Haiyang Wang, Shaoshuai Shi, Ze Yang, Rongyao Fang, Qi Qian, Hongsheng Li, Bernt Schiele, Liwei Wang:
RBGNet: Ray-based Grouping for 3D Object Detection. CVPR 2022: 1100-1109 - [c89]Xiaoyu Chen, Jiachen Hu, Chi Jin, Lihong Li, Liwei Wang:
Understanding Domain Randomization for Sim-to-real Transfer. ICLR 2022 - [c88]Yunchang Yang, Tianhao Wu, Han Zhong, Evrard Garcelon, Matteo Pirotta, Alessandro Lazaric, Liwei Wang, Simon Shaolei Du:
A Reduction-Based Framework for Conservative Bandits and Reinforcement Learning. ICLR 2022 - [c87]Bohang Zhang, Du Jiang, Di He, Liwei Wang:
Boosting the Certified Robustness of L-infinity Distance Nets. ICLR 2022 - [c86]Xiaoyu Chen, Han Zhong, Zhuoran Yang, Zhaoran Wang, Liwei Wang:
Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation. ICML 2022: 3773-3793 - [c85]Tianhao Wu, Yunchang Yang, Han Zhong, Liwei Wang, Simon S. Du, Jiantao Jiao:
Nearly Optimal Policy Optimization with Stable at Any Time Guarantee. ICML 2022: 24243-24265 - [c84]Han Zhong, Wei Xiong, Jiyuan Tan, Liwei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang:
Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets. ICML 2022: 27117-27142 - [c83]Binghui Li, Jikai Jin, Han Zhong, John E. Hopcroft, Liwei Wang:
Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power. NeurIPS 2022 - [c82]Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He:
Your Transformer May Not be as Powerful as You Expect. NeurIPS 2022 - [c81]Haiyang Wang, Lihe Ding, Shaocong Dong, Shaoshuai Shi, Aoxue Li, Jianan Li, Zhenguo Li, Liwei Wang:
CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds. NeurIPS 2022 - [c80]Chuwei Wang, Shanda Li, Di He, Liwei Wang:
Is $L^2$ Physics Informed Loss Always Suitable for Training Physics Informed Neural Network? NeurIPS 2022 - [c79]Bohang Zhang, Du Jiang, Di He, Liwei Wang:
Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective. NeurIPS 2022 - 2021
- [c78]Ke Lin, Zhuoxin Gan, Liwei Wang:
Augmented Partial Mutual Learning with Frame Masking for Video Captioning. AAAI 2021: 2047-2055 - [c77]Hanzhe Hu, Shuai Bai, Aoxue Li, Jinshi Cui, Liwei Wang:
Dense Relation Distillation With Context-Aware Aggregation for Few-Shot Object Detection. CVPR 2021: 10185-10194 - [c76]Hanzhe Hu, Jinshi Cui, Liwei Wang:
Region-aware Contrastive Learning for Semantic Segmentation. ICCV 2021: 16271-16281 - [c75]Xiaoyu Chen, Jiachen Hu, Lihong Li, Liwei Wang:
Efficient Reinforcement Learning in Factored MDPs with Application to Constrained RL. ICLR 2021 - [c74]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 - [c73]Jiachen Hu, Xiaoyu Chen, Chi Jin, Lihong Li, Liwei Wang:
Near-Optimal Representation Learning for Linear Bandits and Linear RL. ICML 2021: 4349-4358 - [c72]Tianhao Wu, Yunchang Yang, Simon S. Du, Liwei Wang:
On Reinforcement Learning with Adversarial Corruption and Its Application to Block MDP. ICML 2021: 11296-11306 - [c71]Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang:
Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons. ICML 2021: 12368-12379 - [c70]Ruiheng Chang, Dong Wang, Haiyan Guo, Jia Ding, Liwei Wang:
Weakly-Supervised Ultrasound Video Segmentation with Minimal Annotations. MICCAI (8) 2021: 648-658 - [c69]Jikai Jin, Bohang Zhang, Haiyang Wang, Liwei Wang:
Non-convex Distributionally Robust Optimization: Non-asymptotic Analysis. NeurIPS 2021: 2771-2782 - [c68]Han Zhong, Jiayi Huang, Lin Yang, Liwei Wang:
Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs. NeurIPS 2021: 15710-15720 - [c67]Hanzhe Hu, Fangyun Wei, Han Hu, Qiwei Ye, Jinshi Cui, Liwei Wang:
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning. NeurIPS 2021: 22106-22118 - [c66]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. NeurIPS 2021: 22795-22807 - [c65]Haotian Ye, Chuanlong Xie, Tianle Cai, Ruichen Li, Zhenguo Li, Liwei Wang:
Towards a Theoretical Framework of Out-of-Distribution Generalization. NeurIPS 2021: 23519-23531 - 2020
- [c64]Dong Wang, Yuan Zhang, Kexin Zhang, Liwei Wang:
FocalMix: Semi-Supervised Learning for 3D Medical Image Detection. CVPR 2020: 3950-3959 - [c63]Yihong Chen, Yue Cao, Han Hu, Liwei Wang:
Memory Enhanced Global-Local Aggregation for Video Object Detection. CVPR 2020: 10334-10343 - [c62]Aoxue Li, Weiran Huang, Xu Lan, Jiashi Feng, Zhenguo Li, Liwei Wang:
Boosting Few-Shot Learning With Adaptive Margin Loss. CVPR 2020: 12573-12581 - [c61]Ze Yang, Yinghao Xu, Han Xue, Zheng Zhang, Raquel Urtasun, Liwei Wang, Stephen Lin, Han Hu:
Dense RepPoints: Representing Visual Objects with Dense Point Sets. ECCV (21) 2020: 227-244 - [c60]Ke Lin, Zhuoxin Gan, Liwei Wang:
Semi-Supervised Learning for Video Captioning. EMNLP (Findings) 2020: 1096-1106 - [c59]Jiadong Lin, Chuanbiao Song, Kun He, Liwei Wang, John E. Hopcroft:
Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks. ICLR 2020 - [c58]Tiange Luo, Kaichun Mo, Zhiao Huang, Jiarui Xu, Siyu Hu, Liwei Wang, Hao Su:
Learning to Group: A Bottom-Up Framework for 3D Part Discovery in Unseen Categories. ICLR 2020 - [c57]Chuanbiao Song, Kun He, Jiadong Lin, Liwei Wang, John E. Hopcroft:
Robust Local Features for Improving the Generalization of Adversarial Training. ICLR 2020 - [c56]Yuanhao Wang, Kefan Dong, Xiaoyu Chen, Liwei Wang:
Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDP. ICLR 2020 - [c55]Yuanhao Wang, Jiachen Hu, Xiaoyu Chen, Liwei Wang:
Distributed Bandit Learning: Near-Optimal Regret with Efficient Communication. ICLR 2020 - [c54]Runtian Zhai, Chen Dan, Di He, Huan Zhang, Boqing Gong, Pradeep Ravikumar, Cho-Jui Hsieh, Liwei Wang:
MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius. ICLR 2020 - [c53]Xiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen, Liwei Wang:
(Locally) Differentially Private Combinatorial Semi-Bandits. ICML 2020: 1757-1767 - [c52]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 - [c51]Dong Wang, Kexin Zhang, Jia Ding, Liwei Wang:
Improve Bone Age Assessment by Learning from Anatomical Local Regions. MICCAI (6) 2020: 631-640 - [c50]Kai Zheng, Tianle Cai, Weiran Huang, Zhenguo Li, Liwei Wang:
Locally Differentially Private (Contextual) Bandits Learning. NeurIPS 2020 - [c49]Yihong Chen, Zheng Zhang, Yue Cao, Liwei Wang, Stephen Lin, Han Hu:
RepPoints v2: Verification Meets Regression for Object Detection. NeurIPS 2020 - [c48]Jingtong Su, Yihang Chen, Tianle Cai, Tianhao Wu, Ruiqi Gao, Liwei Wang, Jason D. Lee:
Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot. NeurIPS 2020 - [c47]Bohang Zhang, Jikai Jin, Cong Fang, Liwei Wang:
Improved Analysis of Clipping Algorithms for Non-convex Optimization. NeurIPS 2020 - 2019
- [c46]Aoxue Li, Tiange Luo, Zhiwu Lu, Tao Xiang, Liwei Wang:
Large-Scale Few-Shot Learning: Knowledge Transfer With Class Hierarchy. CVPR 2019: 7212-7220 - [c45]Zhuohan Li, Zi Lin, Di He, Fei Tian, Tao Qin, Liwei Wang, Tie-Yan Liu:
Hint-Based Training for Non-Autoregressive Machine Translation. EMNLP/IJCNLP (1) 2019: 5707-5712 - [c44]Ze Yang, Liwei Wang:
Learning Relationships for Multi-View 3D Object Recognition. ICCV 2019: 7504-7513 - [c43]Ze Yang, Shaohui Liu, Han Hu, Liwei Wang, Stephen Lin:
RepPoints: Point Set Representation for Object Detection. ICCV 2019: 9656-9665 - [c42]Aoxue Li, Tiange Luo, Tao Xiang, Weiran Huang, Liwei Wang:
Few-Shot Learning With Global Class Representations. ICCV 2019: 9714-9723 - [c41]Jun Gao, Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu:
Representation Degeneration Problem in Training Natural Language Generation Models. ICLR (Poster) 2019 - [c40]Chuanbiao Song, Kun He, Liwei Wang, John E. Hopcroft:
Improving the Generalization of Adversarial Training with Domain Adaptation. ICLR (Poster) 2019 - [c39]Simon S. Du, Jason D. Lee, Haochuan Li, Liwei Wang, Xiyu Zhai:
Gradient Descent Finds Global Minima of Deep Neural Networks. ICML 2019: 1675-1685 - [c38]Linyuan Gong, Di He, Zhuohan Li, Tao Qin, Liwei Wang, Tie-Yan Liu:
Efficient Training of BERT by Progressively Stacking. ICML 2019: 2337-2346 - [c37]Kai Zheng, Haipeng Luo, Ilias Diakonikolas, Liwei Wang:
Equipping Experts/Bandits with Long-term Memory. NeurIPS 2019: 5927-5937 - [c36]Rui Ray Zhang, Xingwu Liu, Yuyi Wang, Liwei Wang:
McDiarmid-Type Inequalities for Graph-Dependent Variables and Stability Bounds. NeurIPS 2019: 10889-10899 - [c35]Ruiqi Gao, Tianle Cai, Haochuan Li, Cho-Jui Hsieh, Liwei Wang, Jason D. Lee:
Convergence of Adversarial Training in Overparametrized Neural Networks. NeurIPS 2019: 13009-13020 - 2018
- [c34]Wenlong Mou, Liwei Wang, Xiyu Zhai, Kai Zheng:
Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints. COLT 2018: 605-638 - [c33]Jiayuan Gu, Han Hu, Liwei Wang, Yichen Wei, Jifeng Dai:
Learning Region Features for Object Detection. ECCV (12) 2018: 392-406 - [c32]Ze Yang, Tiange Luo, Dong Wang, Zhiqiang Hu, Jun Gao, Liwei Wang:
Learning to Navigate for Fine-Grained Classification. ECCV (14) 2018: 438-454 - [c31]Zhuohan Li, Di He, Fei Tian, Wei Chen, Tao Qin, Liwei Wang, Tie-Yan Liu:
Towards Binary-Valued Gates for Robust LSTM Training. ICML 2018: 3001-3010 - [c30]Wenlong Mou, Yuchen Zhou, Jun Gao, Liwei Wang:
Dropout Training, Data-dependent Regularization, and Generalization Bounds. ICML 2018: 3642-3650 - [c29]Chen Dan, Kristoffer Arnsfelt Hansen, He Jiang, Liwei Wang, Yuchen Zhou:
Low Rank Approximation of Binary Matrices: Column Subset Selection and Generalizations. MFCS 2018: 41:1-41:16 - [c28]ChengYue Gong, Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu:
FRAGE: Frequency-Agnostic Word Representation. NeurIPS 2018: 1341-1352 - [c27]Liwei Wang, Lunjia Hu, Jiayuan Gu, Zhiqiang Hu, Yue Wu, Kun He, John E. Hopcroft:
Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation. NeurIPS 2018: 9607-9616 - 2017
- [c26]Wenlong Mou, Liwei Wang:
A Refined Analysis of LSH for Well-dispersed Data Points. ANALCO 2017: 174-182 - [c25]Lunjia Hu, Ruihan Wu, Tianhong Li, Liwei Wang:
Quadratic Upper Bound for Recursive Teaching Dimension of Finite VC Classes. COLT 2017: 1147-1156 - [c24]Kai Zheng, Wenlong Mou, Liwei Wang:
Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible. ICML 2017: 4130-4139 - [c23]Jiaqi Zhang, Kai Zheng, Wenlong Mou, Liwei Wang:
Efficient Private ERM for Smooth Objectives. IJCAI 2017: 3922-3928 - [c22]Jia Ding, Aoxue Li, Zhiqiang Hu, Liwei Wang:
Accurate Pulmonary Nodule Detection in Computed Tomography Images Using Deep Convolutional Neural Networks. MICCAI (3) 2017: 559-567 - [c21]Di He, Hanqing Lu, Yingce Xia, Tao Qin, Liwei Wang, Tie-Yan Liu:
Decoding with Value Networks for Neural Machine Translation. NIPS 2017: 178-187 - [c20]Zhou Lu, Hongming Pu, Feicheng Wang, Zhiqiang Hu, Liwei Wang:
The Expressive Power of Neural Networks: A View from the Width. NIPS 2017: 6231-6239 - 2016
- [c19]Shizhao Sun, Wei Chen, Liwei Wang, Xiaoguang Liu, Tie-Yan Liu:
On the Depth of Deep Neural Networks: A Theoretical View. AAAI 2016: 2066-2072 - [c18]Di He, Yingce Xia, Tao Qin, Liwei Wang, Nenghai Yu, Tie-Yan Liu, Wei-Ying Ma:
Dual Learning for Machine Translation. NIPS 2016: 820-828 - [c17]Tielin Zhang, Yi Zeng, Dongcheng Zhao, Liwei Wang, Yuxuan Zhao, Bo Xu:
HMSNN: Hippocampus inspired Memory Spiking Neural Network. SMC 2016: 2301-2306 - 2015
- [c16]Zhiwu Lu, Xin Gao, Liwei Wang, Ji-Rong Wen, Songfang Huang:
Noise-Robust Semi-Supervised Learning by Large-Scale Sparse Coding. AAAI 2015: 2828-2834 - [c15]Zhiwu Lu, Xin Gao, Songfang Huang, Liwei Wang, Ji-Rong Wen:
Social Image Parsing by Cross-Modal Data Refinement. IJCAI 2015: 2169-2175 - 2014
- [c14]Zhiwu Lu, Liwei Wang, Ji-Rong Wen:
Direct Semantic Analysis for Social Image Classification. AAAI 2014: 1258-1264 - [c13]Wei Chen, Di He, Tie-Yan Liu, Tao Qin, Yixin Tao, Liwei Wang:
Generalized second price auction with probabilistic broad match. EC 2014: 39-56 - 2013
- [c12]Yining Wang, Liwei Wang, Yuanzhi Li, Di He, Tie-Yan Liu:
A Theoretical Analysis of NDCG Type Ranking Measures. COLT 2013: 25-54 - [c11]Di He, Wei Chen, Liwei Wang, Tie-Yan Liu:
A Game-Theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search. IJCAI 2013: 206-212 - [c10]Ziteng Wang, Kai Fan, Jiaqi Zhang, Liwei Wang:
Efficient Algorithm for Privately Releasing Smooth Queries. NIPS 2013: 782-790 - 2012
- [c9]Kai Fan, Hongyi Zhang, Yu Zang, Liwei Wang:
Estimation Based on RBM from Label Proportions in Large Group Case. IScIDE 2012: 622-629 - [c8]Chi Jin, Liwei Wang:
Dimensionality Dependent PAC-Bayes Margin Bound. NIPS 2012: 1043-1051 - 2011
- [c7]Mingyang Jiang, Chunxiao Li, Zirui Deng, Jufu Feng, Liwei Wang:
Learning from error: A two-level combined model for image classification. ACPR 2011: 677-680 - 2010
- [c6]Mingyang Jiang, Chunxiao Li, Jufu Feng, Liwei Wang:
Segmentation via NCuts and Lossy Minimum Description Length: A Unified Approach. ACCV (3) 2010: 213-224 - [c5]Mingyang Jiang, Chunxiao Li, Jufu Feng, Liwei Wang:
Towards Hypothesis Testing and Lossy Minimum Description Length: A Unified Segmentation Framework. ACCV (3) 2010: 343-354 - 2009
- [c4]Bing Sun, Jufu Feng, Liwei Wang:
Learning IMED via shift-invariant transformation. CVPR 2009: 1398-1405 - 2008
- [c3]Liwei Wang, Masashi Sugiyama, Cheng Yang, Zhi-Hua Zhou, Jufu Feng:
On the Margin Explanation of Boosting Algorithms. COLT 2008: 479-490 - 2007
- [c2]Liwei Wang, Jufu Feng:
Rademacher Margin Complexity. COLT 2007: 620-621 - [c1]Liwei Wang, Cheng Yang, Jufu Feng:
On learning with dissimilarity functions. ICML 2007: 991-998
Informal and Other Publications
- 2024
- [i108]Zhenyu He, Guhao Feng, Shengjie Luo, Kai Yang, Di He, Jingjing Xu, Zhi Zhang, Hongxia Yang, Liwei Wang:
Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation. CoRR abs/2401.16421 (2024) - [i107]Ruichen Li, Chuwei Wang, Haotian Ye, Di He, Liwei Wang:
DOF: Accelerating High-order Differential Operators with Forward Propagation. CoRR abs/2402.09730 (2024) - [i106]Kai Yang, Jan Ackermann, Zhenyu He, Guhao Feng, Bohang Zhang, Yunzhen Feng, Qiwei Ye, Di He, Liwei Wang:
Do Efficient Transformers Really Save Computation? CoRR abs/2402.13934 (2024) - 2023
- [i105]Haiyang Wang, Chen Shi, Shaoshuai Shi, Meng Lei, Sen Wang, Di He, Bernt Schiele, Liwei Wang:
DSVT: Dynamic Sparse Voxel Transformer with Rotated Sets. CoRR abs/2301.06051 (2023) - [i104]Bohang Zhang, Shengjie Luo, Liwei Wang, Di He:
Rethinking the Expressive Power of GNNs via Graph Biconnectivity. CoRR abs/2301.09505 (2023) - [i103]Yunchang Yang, Han Zhong, Tianhao Wu, Bin Liu, Liwei Wang, Simon S. Du:
A Reduction-based Framework for Sequential Decision Making with Delayed Feedback. CoRR abs/2302.01477 (2023) - [i102]Bohang Zhang, Guhao Feng, Yiheng Du, Di He, Liwei Wang:
A Complete Expressiveness Hierarchy for Subgraph GNNs via Subgraph Weisfeiler-Lehman Tests. CoRR abs/2302.07090 (2023) - [i101]Han Zhong, Jiachen Hu, Yecheng Xue, Tongyang Li, Liwei Wang:
Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret. CoRR abs/2302.10796 (2023) - [i100]Guhao Feng, Bohang Zhang, Yuntian Gu, Haotian Ye, Di He, Liwei Wang:
Towards Revealing the Mystery behind Chain of Thought: a Theoretical Perspective. CoRR abs/2305.15408 (2023) - [i99]Jiayi Huang, Han Zhong, Liwei Wang, Lin F. Yang:
Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds. CoRR abs/2306.06836 (2023) - [i98]Ruichen Li, Haotian Ye, Du Jiang, Xuelan Wen, Chuwei Wang, Zhe Li, Xiang Li, Di He, Ji Chen, Weiluo Ren, Liwei Wang:
Forward Laplacian: A New Computational Framework for Neural Network-based Variational Monte Carlo. CoRR abs/2307.08214 (2023) - [i97]Pengyun Yue, Hanzhen Zhao, Cong Fang, Di He, Liwei Wang, Zhouchen Lin, Song-Chun Zhu:
CORE: Common Random Reconstruction for Distributed Optimization with Provable Low Communication Complexity. CoRR abs/2309.13307 (2023) - [i96]Jiayi Huang, Han Zhong, Liwei Wang, Lin F. Yang:
Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation. CoRR abs/2312.04464 (2023) - 2022
- [i95]Han Zhong, Wei Xiong, Jiyuan Tan, Liwei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang:
Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets. CoRR abs/2202.07511 (2022) - [i94]Di He, Wenlei Shi, Shanda Li, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu:
Learning Physics-Informed Neural Networks without Stacked Back-propagation. CoRR abs/2202.09340 (2022) - [i93]Ruichen Li, Binghui Li, Qi Qian, Liwei Wang:
Reconstruction Task Finds Universal Winning Tickets. CoRR abs/2202.11484 (2022) - [i92]Haiyang Wang, Shaoshuai Shi, Ze Yang, Rongyao Fang, Qi Qian, Hongsheng Li, Bernt Schiele, Liwei Wang:
RBGNet: Ray-based Grouping for 3D Object Detection. CoRR abs/2204.02251 (2022) - [i91]Xiaoyu Chen, Han Zhong, Zhuoran Yang, Zhaoran Wang, Liwei Wang:
Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation. CoRR abs/2205.11140 (2022) - [i90]Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He:
Your Transformer May Not be as Powerful as You Expect. CoRR abs/2205.13401 (2022) - [i89]Binghui Li, Jikai Jin, Han Zhong, John E. Hopcroft, Liwei Wang:
Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power. CoRR abs/2205.13863 (2022) - [i88]Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Liwei Wang, Tong Zhang:
Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game. CoRR abs/2205.15512 (2022) - [i87]Chuwei Wang, Shanda Li, Di He, Liwei Wang:
Is L2 Physics-Informed Loss Always Suitable for Training Physics-Informed Neural Network? CoRR abs/2206.02016 (2022) - [i86]Shengjie Luo, Tianlang Chen, Yixian Xu, Shuxin Zheng, Tie-Yan Liu, Di He, Liwei Wang:
One Transformer Can Understand Both 2D & 3D Molecular Data. CoRR abs/2210.01765 (2022) - [i85]Bohang Zhang, Du Jiang, Di He, Liwei Wang:
Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective. CoRR abs/2210.01787 (2022) - [i84]Haiyang Wang, Lihe Ding, Shaocong Dong, Shaoshuai Shi, Aoxue Li, Jianan Li, Zhenguo Li, Liwei Wang:
CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds. CoRR abs/2210.04264 (2022) - [i83]Quanlin Wu, Hang Ye, Yuntian Gu, Huishuai Zhang, Liwei Wang, Di He:
Denoising Masked AutoEncoders are Certifiable Robust Vision Learners. CoRR abs/2210.06983 (2022) - [i82]Haotian Ye, Xiaoyu Chen, Liwei Wang, Simon S. Du:
On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness. CoRR abs/2210.10464 (2022) - [i81]Jiachen Hu, Han Zhong, Chi Jin, Liwei Wang:
Provable Sim-to-real Transfer in Continuous Domain with Partial Observations. CoRR abs/2210.15598 (2022) - [i80]Han Zhong, Wei Xiong, Sirui Zheng, Liwei Wang, Zhaoran Wang, Zhuoran Yang, Tong Zhang:
GEC: A Unified Framework for Interactive Decision Making in MDP, POMDP, and Beyond. CoRR abs/2211.01962 (2022) - 2021
- [i79]Jiachen Hu, Xiaoyu Chen, Chi Jin, Lihong Li, Liwei Wang:
Near-optimal Representation Learning for Linear Bandits and Linear RL. CoRR abs/2102.04132 (2021) - [i78]Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang:
Towards Certifying 𝓁∞ Robustness using Neural Networks with 𝓁∞-dist Neurons. CoRR abs/2102.05363 (2021) - [i77]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) - [i76]Hanzhe Hu, Shuai Bai, Aoxue Li, Jinshi Cui, Liwei Wang:
Dense Relation Distillation with Context-aware Aggregation for Few-Shot Object Detection. CoRR abs/2103.17115 (2021) - [i75]Haotian Ye, Chuanlong Xie, Tianle Cai, Ruichen Li, Zhenguo Li, Liwei Wang:
Towards a Theoretical Framework of Out-of-Distribution Generalization. CoRR abs/2106.04496 (2021) - [i74]Yunchang Yang, Tianhao Wu, Han Zhong, Evrard Garcelon, Matteo Pirotta, Alessandro Lazaric, Liwei Wang, Simon S. Du:
A Unified Framework for Conservative Exploration. CoRR abs/2106.11692 (2021) - [i73]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) - [i72]Xiaosen Wang, Chuanbiao Song, Liwei Wang, Kun He:
Multi-stage Optimization based Adversarial Training. CoRR abs/2106.15357 (2021) - [i71]Haiyang Wang, Wenguan Wang, Xizhou Zhu, Jifeng Dai, Liwei Wang:
Collaborative Visual Navigation. CoRR abs/2107.01151 (2021) - [i70]Xiaoyu Chen, Jiachen Hu, Chi Jin, Lihong Li, Liwei Wang:
Understanding Domain Randomization for Sim-to-real Transfer. CoRR abs/2110.03239 (2021) - [i69]Hanzhe Hu, Fangyun Wei, Han Hu, Qiwei Ye, Jinshi Cui, Liwei Wang:
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning. CoRR abs/2110.05474 (2021) - [i68]Bohang Zhang, Du Jiang, Di He, Liwei Wang:
Boosting the Certified Robustness of L-infinity Distance Nets. CoRR abs/2110.06850 (2021) - [i67]Jikai Jin, Bohang Zhang, Haiyang Wang, Liwei Wang:
Non-convex Distributionally Robust Optimization: Non-asymptotic Analysis. CoRR abs/2110.12459 (2021) - [i66]Han Zhong, Jiayi Huang, Lin F. Yang, Liwei Wang:
Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs. CoRR abs/2110.13876 (2021) - [i65]Tianhao Wu, Yunchang Yang, Han Zhong, Liwei Wang, Simon S. Du, Jiantao Jiao:
Nearly Optimal Policy Optimization with Stable at Any Time Guarantee. CoRR abs/2112.10935 (2021) - 2020
- [i64]Runtian Zhai, Chen Dan, Di He, Huan Zhang, Boqing Gong, Pradeep Ravikumar, Cho-Jui Hsieh, Liwei Wang:
MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius. CoRR abs/2001.02378 (2020) - [i63]Wei Chen, Liwei Wang, Haoyu Zhao, Kai Zheng:
Combinatorial Semi-Bandit in the Non-Stationary Environment. CoRR abs/2002.03580 (2020) - [i62]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) - [i61]Tiange Luo, Kaichun Mo, Zhiao Huang, Jiarui Xu, Siyu Hu, Liwei Wang, Hao Su:
Learning to Group: A Bottom-Up Framework for 3D Part Discovery in Unseen Categories. CoRR abs/2002.06478 (2020) - [i60]Dong Wang, Yuan Zhang, Kexin Zhang, Liwei Wang:
FocalMix: Semi-Supervised Learning for 3D Medical Image Detection. CoRR abs/2003.09108 (2020) - [i59]Yihong Chen, Yue Cao, Han Hu, Liwei Wang:
Memory Enhanced Global-Local Aggregation for Video Object Detection. CoRR abs/2003.12063 (2020) - [i58]Dong Wang, Kexin Zhang, Jia Ding, Liwei Wang:
Improve bone age assessment by learning from anatomical local regions. CoRR abs/2005.13452 (2020) - [i57]Aoxue Li, Weiran Huang, Xu Lan, Jiashi Feng, Zhenguo Li, Liwei Wang:
Boosting Few-Shot Learning With Adaptive Margin Loss. CoRR abs/2005.13826 (2020) - [i56]Kai Zheng, Tianle Cai, Weiran Huang, Zhenguo Li, Liwei Wang:
Locally Differentially Private (Contextual) Bandits Learning. CoRR abs/2006.00701 (2020) - [i55]Xiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen, Liwei Wang:
(Locally) Differentially Private Combinatorial Semi-Bandits. CoRR abs/2006.00706 (2020) - [i54]Ke Lin, Zhuoxin Gan, Liwei Wang:
Multi-modal Feature Fusion with Feature Attention for VATEX Captioning Challenge 2020. CoRR abs/2006.03315 (2020) - [i53]Zhenhui Xu, Linyuan Gong, Guolin Ke, Di He, Shuxin Zheng, Liwei Wang, Jiang Bian, Tie-Yan Liu:
MC-BERT: Efficient Language Pre-Training via a Meta Controller. CoRR abs/2006.05744 (2020) - [i52]Yihong Chen, Zheng Zhang, Yue Cao, Liwei Wang, Stephen Lin, Han Hu:
RepPoints V2: Verification Meets Regression for Object Detection. CoRR abs/2007.08508 (2020) - [i51]Yunzhen Feng, Runtian Zhai, Di He, Liwei Wang, Bin Dong:
Transferred Discrepancy: Quantifying the Difference Between Representations. CoRR abs/2007.12446 (2020) - [i50]Tiange Luo, Tianle Cai, Mengxiao Zhang, Siyu Chen, Liwei Wang:
RANDOM MASK: Towards Robust Convolutional Neural Networks. CoRR abs/2007.14249 (2020) - [i49]Xiaoyu Chen, Jiachen Hu, Lihong Li, Liwei Wang:
Efficient Reinforcement Learning in Factored MDPs with Application to Constrained RL. CoRR abs/2008.13319 (2020) - [i48]Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang:
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training. CoRR abs/2009.03294 (2020) - [i47]Jingtong Su, Yihang Chen, Tianle Cai, Tianhao Wu, Ruiqi Gao, Liwei Wang, Jason D. Lee:
Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot. CoRR abs/2009.11094 (2020) - [i46]Bohang Zhang, Jikai Jin, Cong Fang, Liwei Wang:
Improved Analysis of Clipping Algorithms for Non-convex Optimization. CoRR abs/2010.02519 (2020) - 2019
- [i45]Kefan Dong, Yuanhao Wang, Xiaoyu Chen, Liwei Wang:
Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDP. CoRR abs/1901.09311 (2019) - [i44]Jun Gao, Xiao Li, Liwei Wang, Sanja Fidler, Stephen Lin:
Mimicking the In-Camera Color Pipeline for Camera-Aware Object Compositing. CoRR abs/1903.11248 (2019) - [i43]Yuanhao Wang, Jiachen Hu, Xiaoyu Chen, Liwei Wang:
Distributed Bandit Learning: How Much Communication is Needed to Achieve (Near) Optimal Regret. CoRR abs/1904.06309 (2019) - [i42]Ze Yang, Shaohui Liu, Han Hu, Liwei Wang, Stephen Lin:
RepPoints: Point Set Representation for Object Detection. CoRR abs/1904.11490 (2019) - [i41]Tianle Cai, Ruiqi Gao, Jikai Hou, Siyu Chen, Dong Wang, Di He, Zhihua Zhang, Liwei Wang:
A Gram-Gauss-Newton Method Learning Overparameterized Deep Neural Networks for Regression Problems. CoRR abs/1905.11675 (2019) - [i40]Kai Zheng, Haipeng Luo, Ilias Diakonikolas, Liwei Wang:
Equipping Experts/Bandits with Long-term Memory. CoRR abs/1905.12950 (2019) - [i39]Runtian Zhai, Tianle Cai, Di He, Chen Dan, Kun He, John E. Hopcroft, Liwei Wang:
Adversarially Robust Generalization Just Requires More Unlabeled Data. CoRR abs/1906.00555 (2019) - [i38]Yiping Lu, Zhuohan Li, Di He, Zhiqing Sun, Bin Dong, Tao Qin, Liwei Wang, Tie-Yan Liu:
Understanding and Improving Transformer From a Multi-Particle Dynamic System Point of View. CoRR abs/1906.02762 (2019) - [i37]Ruiqi Gao, Tianle Cai, Haochuan Li, Liwei Wang, Cho-Jui Hsieh, Jason D. Lee:
Convergence of Adversarial Training in Overparametrized Networks. CoRR abs/1906.07916 (2019) - [i36]Jun Gao, Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu:
Representation Degeneration Problem in Training Natural Language Generation Models. CoRR abs/1907.12009 (2019) - [i35]Tiange Luo, Aoxue Li, Tao Xiang, Weiran Huang, Liwei Wang:
Few-Shot Learning with Global Class Representations. CoRR abs/1908.05257 (2019) - [i34]Jiadong Lin, Chuanbiao Song, Kun He, Liwei Wang, John E. Hopcroft:
Nesterov Accelerated Gradient and Scale Invariance for Improving Transferability of Adversarial Examples. CoRR abs/1908.06281 (2019) - [i33]Rui Ray Zhang, Xingwu Liu, Yuyi Wang, Liwei Wang:
McDiarmid-Type Inequalities for Graph-Dependent Variables and Stability Bounds. CoRR abs/1909.02330 (2019) - [i32]Zhuohan Li, Zi Lin, Di He, Fei Tian, Tao Qin, Liwei Wang, Tie-Yan Liu:
Hint-Based Training for Non-Autoregressive Machine Translation. CoRR abs/1909.06708 (2019) - [i31]Chuanbiao Song, Kun He, Jiadong Lin, Liwei Wang, John E. Hopcroft:
Robust Local Features for Improving the Generalization of Adversarial Training. CoRR abs/1909.10147 (2019) - [i30]Jinchen Xuan, Yunchang Yang, Ze Yang, Di He, Liwei Wang:
On the Anomalous Generalization of GANs. CoRR abs/1909.12638 (2019) - [i29]Tiange Luo, Tianle Cai, Mengxiao Zhang, Siyu Chen, Di He, Liwei Wang:
Defective Convolutional Layers Learn Robust CNNs. CoRR abs/1911.08432 (2019) - [i28]Ze Yang, Yinghao Xu, Han Xue, Zheng Zhang, Raquel Urtasun, Liwei Wang, Stephen Lin, Han Hu:
Dense RepPoints: Representing Visual Objects with Dense Point Sets. CoRR abs/1912.11473 (2019) - 2018
- [i27]Jiayuan Gu, Han Hu, Liwei Wang, Yichen Wei, Jifeng Dai:
Learning Region Features for Object Detection. CoRR abs/1803.07066 (2018) - [i26]Zhuohan Li, Di He, Fei Tian, Wei Chen, Tao Qin, Liwei Wang, Tie-Yan Liu:
Towards Binary-Valued Gates for Robust LSTM Training. CoRR abs/1806.02988 (2018) - [i25]Ze Yang, Tiange Luo, Dong Wang, Zhiqiang Hu, Jun Gao, Liwei Wang:
Learning to Navigate for Fine-grained Classification. CoRR abs/1809.00287 (2018) - [i24]ChengYue Gong, Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu:
FRAGE: Frequency-Agnostic Word Representation. CoRR abs/1809.06858 (2018) - [i23]Chuanbiao Song, Kun He, Liwei Wang, John E. Hopcroft:
Improving the Generalization of Adversarial Training with Domain Adaptation. CoRR abs/1810.00740 (2018) - [i22]Aoxue Li, Zhiwu Lu, Jiechao Guan, Tao Xiang, Liwei Wang, Ji-Rong Wen:
Transferrable Feature and Projection Learning with Class Hierarchy for Zero-Shot Learning. CoRR abs/1810.08329 (2018) - [i21]Liwei Wang, Lunjia Hu, Jiayuan Gu, Yue Wu, Zhiqiang Hu, Kun He, John E. Hopcroft:
Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation. CoRR abs/1810.11750 (2018) - [i20]Simon S. Du, Jason D. Lee, Haochuan Li, Liwei Wang, Xiyu Zhai:
Gradient Descent Finds Global Minima of Deep Neural Networks. CoRR abs/1811.03804 (2018) - 2017
- [i19]Lunjia Hu, Ruihan Wu, Tianhong Li, Liwei Wang:
Quadratic Upper Bound for Recursive Teaching Dimension of Finite VC Classes. CoRR abs/1702.05677 (2017) - [i18]Jiaqi Zhang, Kai Zheng, Wenlong Mou, Liwei Wang:
Efficient Private ERM for Smooth Objectives. CoRR abs/1703.09947 (2017) - [i17]Kai Zheng, Wenlong Mou, Liwei Wang:
Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible. CoRR abs/1706.03316 (2017) - [i16]Jia Ding, Aoxue Li, Zhiqiang Hu, Liwei Wang:
Accurate Pulmonary Nodule Detection in Computed Tomography Images Using Deep Convolutional Neural Networks. CoRR abs/1706.04303 (2017) - [i15]Aoxue Li, Zhiwu Lu, Liwei Wang, Tao Xiang, Xinqi Li, Ji-Rong Wen:
Zero-Shot Fine-Grained Classification by Deep Feature Learning with Semantics. CoRR abs/1707.00785 (2017) - [i14]Wenlong Mou, Liwei Wang, Xiyu Zhai, Kai Zheng:
Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints. CoRR abs/1707.05947 (2017) - [i13]Zhou Lu, Hongming Pu, Feicheng Wang, Zhiqiang Hu, Liwei Wang:
The Expressive Power of Neural Networks: A View from the Width. CoRR abs/1709.02540 (2017) - 2016
- [i12]Yingce Xia, Di He, Tao Qin, Liwei Wang, Nenghai Yu, Tie-Yan Liu, Wei-Ying Ma:
Dual Learning for Machine Translation. CoRR abs/1611.00179 (2016) - [i11]Wenlong Mou, Liwei Wang:
A Refined Analysis of LSH for Well-dispersed Data Points. CoRR abs/1612.04571 (2016) - [i10]Wenlong Mou, Zhi Wang, Liwei Wang:
Stable Memory Allocation in the Hippocampus: Fundamental Limits and Neural Realization. CoRR abs/1612.04659 (2016) - 2015
- [i9]Zhiwu Lu, Liwei Wang:
Pairwise Constraint Propagation on Multi-View Data. CoRR abs/1501.04284 (2015) - [i8]Zhiwu Lu, Liwei Wang, Ji-Rong Wen:
Image classification by visual bag-of-words refinement and reduction. CoRR abs/1501.04292 (2015) - [i7]Shizhao Sun, Wei Chen, Liwei Wang, Tie-Yan Liu:
Large Margin Deep Neural Networks: Theory and Algorithms. CoRR abs/1506.05232 (2015) - [i6]Chen Dan, Kristoffer Arnsfelt Hansen, He Jiang, Liwei Wang, Yuchen Zhou:
On Low Rank Approximation of Binary Matrices. CoRR abs/1511.01699 (2015) - 2014
- [i5]Chi Jin, Ziteng Wang, Junliang Huang, Yiqiao Zhong, Liwei Wang:
Differentially Private Data Releasing for Smooth Queries with Synthetic Database Output. CoRR abs/1401.0987 (2014) - [i4]Zhiwu Lu, Liwei Wang:
Can Image-Level Labels Replace Pixel-Level Labels for Image Parsing. CoRR abs/1403.1626 (2014) - [i3]Wei Chen, Di He, Tie-Yan Liu, Tao Qin, Yixin Tao, Liwei Wang:
Generalized Second Price Auction with Probabilistic Broad Match. CoRR abs/1404.3828 (2014) - [i2]Di He, Wei Chen, Liwei Wang, Tie-Yan Liu:
A Game-theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search. CoRR abs/1406.0728 (2014) - 2013
- [i1]Yining Wang, Liwei Wang, Yuanzhi Li, Di He, Tie-Yan Liu, Wei Chen:
A Theoretical Analysis of NDCG Type Ranking Measures. CoRR abs/1304.6480 (2013)
Coauthor Index
Simon S. Du
aka: Simon Shaolei Du
aka: Simon Shaolei Du
[j14] [c102] [c101] [c98] [c97] [c96] [c94] [c93] [c87] [c82] [c80] [c79] [c74] [c71] [c66] [c54] [c52] [c45] [c41] [c38] [c31] [c28] [c21] [c18] [c13] [c12] [c11] [i108] [i107] [i106] [i105] [i104] [i102] [i100] [i98] [i97] [i94] [i90] [i87] [i86] [i85] [i83] [i78] [i77] [i73] [i68] [i64] [i62] [i53] [i51] [i48] [i41] [i39] [i38] [i36] [i32] [i30] [i29] [i26] [i24] [i12] [i3] [i2] [i1]
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