Jin, Jikai

12 publications

NeurIPS 2025 It’s Hard to Be Normal: The Impact of Noise on Structure-Agnostic Estimation Jikai Jin, Lester Mackey, Vasilis Syrgkanis

NeurIPS 2025 Solving Inequality Proofs with Large Language Models Pan Lu, Jiayi Sheng, Luna Lyu, Jikai Jin, Tony Xia, Alex Gu, James Zou

COLT 2025 Structure-Agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation (Extended Abstract) Jikai Jin, Vasilis Syrgkanis

ICLR 2024 Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking Kaifeng Lyu, Jikai Jin, Zhiyuan Li, Simon Shaolei Du, Jason D. Lee, Wei Hu

NeurIPS 2024 Learning Linear Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity Jikai Jin, Vasilis Syrgkanis

ICLR 2023 Minimax Optimal Kernel Operator Learning via Multilevel Training Jikai Jin, Yiping Lu, Jose Blanchet, Lexing Ying

ICML 2023 Understanding Incremental Learning of Gradient Descent: A Fine-Grained Analysis of Matrix Sensing Jikai Jin, Zhiyuan Li, Kaifeng Lyu, Simon Shaolei Du, Jason D. Lee

NeurIPSW 2022 Minimax Optimal Kernel Operator Learning via Multilevel Training Jikai Jin, Yiping Lu, Jose Blanchet, Lexing Ying

COLT 2022 Understanding Riemannian Acceleration via a Proximal Extragradient Framework Jikai Jin, Suvrit Sra

NeurIPS 2022 Why Robust Generalization in Deep Learning Is Difficult: Perspective of Expressive Power Binghui Li, Jikai Jin, Han Zhong, John Hopcroft, Liwei Wang

NeurIPS 2021 Non-Convex Distributionally Robust Optimization: Non-Asymptotic Analysis Jikai Jin, Bohang Zhang, Haiyang Wang, Liwei Wang

NeurIPS 2020 Improved Analysis of Clipping Algorithms for Non-Convex Optimization Bohang Zhang, Jikai Jin, Cong Fang, Liwei Wang