Strategy-Proof Data Auctions with Negative Externalities: (Extended Abstract). - Xiang Wang 011; Zhenzhe Zheng; Fan Wu 006; Xiaoju Dong; Shaojie Tang 001; Guihai Chen (AAMAS, 2016)

Efficient Auctions with Identity-Dependent Negative Externalities. - Chaoli Zhang 003; Xiang Wang 011; Fan Wu 006; Xiaohui Bei (AAMAS, 2018)

Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization. - Rong Ge 001; Zhize Li; Weiyao Wang 001; Xiang Wang 011 (COLT, 2019)

Learning Two-layer Neural Networks with Symmetric Inputs. - Rong Ge 001; Rohith Kuditipudi; Zhize Li; Xiang Wang 011 (ICLR (Poster), 2019)

Explaining Landscape Connectivity of Low-cost Solutions for Multilayer Nets. - Rohith Kuditipudi; Xiang Wang 011; Holden Lee; Yi Zhang 074; Zhiyuan Li 005; Wei Hu 014; Rong Ge 001; Sanjeev Arora (NeurIPS, 2019)

Beyond Lazy Training for Over-parameterized Tensor Decomposition. - Xiang Wang 011; Chenwei Wu 002; Jason D. Lee; Tengyu Ma 001; Rong Ge 001 (NeurIPS, 2020)

Guarantees for Tuning the Step Size using a Learning-to-Learn Approach. - Xiang Wang 011; Shuai Yuan; Chenwei Wu 002; Rong Ge 001 (ICML, 2021)

Understanding Deflation Process in Over-parametrized Tensor Decomposition. - Rong Ge 001; Yunwei Ren; Xiang Wang 011; Mo Zhou (NeurIPS, 2021)

Towards Demystifying Representation Learning with Non-contrastive Self-supervision. - Xiang Wang 011; Xinlei Chen; Simon S. Du; Yuandong Tian (CoRR, 2021)

Towards Understanding the Data Dependency of Mixup-style Training. - Muthu Chidambaram; Xiang Wang 011; Yuzheng Hu; Chenwei Wu 002; Rong Ge 001 (ICLR, 2022)

Understanding Edge-of-Stability Training Dynamics with a Minimalist Example. - Xingyu Zhu 003; Zixuan Wang; Xiang Wang 011; Mo Zhou; Rong Ge 001 (ICLR, 2023)

Plateau in Monotonic Linear Interpolation - A "Biased" View of Loss Landscape for Deep Networks. - Xiang Wang 011; Annie N. Wang; Mo Zhou; Rong Ge 001 (ICLR, 2023)

Provably Learning Diverse Features in Multi-View Data with Midpoint Mixup. - Muthu Chidambaram; Xiang Wang 011; Chenwei Wu 002; Rong Ge 001 (ICML, 2023)