Xiang Wang - RankMe

23 papers A* 9A 2Journal 11Unranked 1

Year	Rank	Type	Title / Venue / Authors
2023	A*	`conf`	Plateau in Monotonic Linear Interpolation - A "Biased" View of Loss Landscape for Deep Networks. ICLR Xiang Wang, Annie N. Wang, Mo Zhou, Rong Ge
2023	A*	`conf`	Provably Learning Diverse Features in Multi-View Data with Midpoint Mixup. ICML Muthu Chidambaram, Xiang Wang, Chenwei Wu, Rong Ge
2023	A*	`conf`	Understanding Edge-of-Stability Training Dynamics with a Minimalist Example. ICLR Xingyu Zhu, Zixuan Wang, Xiang Wang, Mo Zhou, Rong Ge
2022	J	`jnl`	Plateau in Monotonic Linear Interpolation - A "Biased" View of Loss Landscape for Deep Networks. CoRR Xiang Wang, Annie N. Wang, Mo Zhou, Rong Ge
2022	J	`jnl`	Provably Learning Diverse Features in Multi-View Data with Midpoint Mixup. CoRR Muthu Chidambaram, Xiang Wang, Chenwei Wu, Rong Ge
2022	A*	`conf`	Towards Understanding the Data Dependency of Mixup-style Training. ICLR Muthu Chidambaram, Xiang Wang, Yuzheng Hu, Chenwei Wu, Rong Ge
2022	J	`jnl`	Understanding Edge-of-Stability Training Dynamics with a Minimalist Example. CoRR Xingyu Zhu, Zixuan Wang, Xiang Wang, Mo Zhou, Rong Ge
2021	A*	`conf`	Guarantees for Tuning the Step Size using a Learning-to-Learn Approach. ICML Xiang Wang, Shuai Yuan, Chenwei Wu, Rong Ge
2021	J	`jnl`	Towards Demystifying Representation Learning with Non-contrastive Self-supervision. CoRR Xiang Wang, Xinlei Chen, Simon S. Du, Yuandong Tian
2021	J	`jnl`	Towards Understanding the Data Dependency of Mixup-style Training. CoRR Muthu Chidambaram, Xiang Wang, Yuzheng Hu, Chenwei Wu, Rong Ge
2021	A*	`conf`	Understanding Deflation Process in Over-parametrized Tensor Decomposition. NeurIPS Rong Ge, Yunwei Ren, Xiang Wang, Mo Zhou
2021	J	`jnl`	Understanding Deflation Process in Over-parametrized Tensor Decomposition. CoRR Rong Ge, Yunwei Ren, Xiang Wang, Mo Zhou
2020	A*	`conf`	Beyond Lazy Training for Over-parameterized Tensor Decomposition. NeurIPS Xiang Wang, Chenwei Wu, Jason D. Lee, Tengyu Ma, Rong Ge
2020	J	`jnl`	Beyond Lazy Training for Over-parameterized Tensor Decomposition. CoRR Xiang Wang, Chenwei Wu, Jason D. Lee, Tengyu Ma, Rong Ge
2020	J	`jnl`	Guarantees for Tuning the Step Size using a Learning-to-Learn Approach. CoRR Xiang Wang, Shuai Yuan, Chenwei Wu, Rong Ge
2019	A*	`conf`	Explaining Landscape Connectivity of Low-cost Solutions for Multilayer Nets. NeurIPS Rohith Kuditipudi, Xiang Wang, Holden Lee, Yi Zhang, Zhiyuan Li, Wei Hu, Rong Ge, Sanjeev Arora
2019	J	`jnl`	Explaining Landscape Connectivity of Low-cost Solutions for Multilayer Nets. CoRR Rohith Kuditipudi, Xiang Wang, Holden Lee, Yi Zhang, Zhiyuan Li, Wei Hu, Sanjeev Arora, Rong Ge
2019	—	`conf`	Learning Two-layer Neural Networks with Symmetric Inputs. ICLR (Poster) Rong Ge, Rohith Kuditipudi, Zhize Li, Xiang Wang
2019	A*	`conf`	Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization. COLT Rong Ge, Zhize Li, Weiyao Wang, Xiang Wang
2019	J	`jnl`	Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization. CoRR Rong Ge, Zhize Li, Weiyao Wang, Xiang Wang
2018	A	`conf`	Efficient Auctions with Identity-Dependent Negative Externalities. AAMAS Chaoli Zhang, Xiang Wang, Fan Wu, Xiaohui Bei
2018	J	`jnl`	Learning Two-layer Neural Networks with Symmetric Inputs. CoRR Rong Ge, Rohith Kuditipudi, Zhize Li, Xiang Wang
2016	A	`conf`	Strategy-Proof Data Auctions with Negative Externalities: (Extended Abstract). AAMAS Xiang Wang, Zhenzhe Zheng, Fan Wu, Xiaoju Dong, Shaojie Tang, Guihai Chen