Stebėti
Jikai Jin
Pavadinimas
Cituota
Cituota
Metai
Improved analysis of clipping algorithms for non-convex optimization
B Zhang, J Jin, C Fang, L Wang
Advances in Neural Information Processing Systems 33, 15511-15521, 2020
612020
Non-convex distributionally robust optimization: Non-asymptotic analysis
J Jin, B Zhang, H Wang, L Wang
Advances in Neural Information Processing Systems 34, 2771-2782, 2021
352021
Understanding incremental learning of gradient descent: A fine-grained analysis of matrix sensing
J Jin, Z Li, K Lyu, SS Du, JD Lee
International Conference on Machine Learning, 15200-15238, 2023
282023
Why robust generalization in deep learning is difficult: Perspective of expressive power
B Li, J Jin, H Zhong, J Hopcroft, L Wang
Advances in Neural Information Processing Systems 35, 4370-4384, 2022
212022
Dichotomy of early and late phase implicit biases can provably induce grokking
K Lyu, J Jin, Z Li, SS Du, JD Lee, W Hu
The Twelfth International Conference on Learning Representations, 2024
152024
Minimax Optimal Kernel Operator Learning via Multilevel Training
J Jin, Y Lu, J Blanchet, L Ying
The Eleventh International Conference on Learning Representations, 2023
102023
Understanding Riemannian Acceleration via a Proximal Extragradient Framework
J Jin, S Sra
Proceedings of Thirty Fifth Conference on Learning Theory, PMLR 178, 2924-2962, 2022
10*2022
On the convergence of first order methods for quasar-convex optimization
J Jin
12th Annual Workshop on Optimization for Machine Learning, 2020
72020
Learning causal representations from general environments: Identifiability and intrinsic ambiguity
J Jin, V Syrgkanis
arXiv preprint arXiv:2311.12267, 2023
42023
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation
J Jin, V Syrgkanis
arXiv preprint arXiv:2402.14264, 2024
12024
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Straipsniai 1–10