10 citations · 26 across the 13 of their papers we have counts for
Showing 2023Show all
3 papers · 1 filter
cs.LG2023★ 2 cited
Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking
Kaifeng Lyu, Jikai Jin, Zhiyuan Li +3
Recent work by Power et al. (2022) highlighted a surprising "grokking" phenomenon in learning arithmetic tasks: a neural net first "memorizes" the training set, resulting in perfec…
cs.LG2023
Learning Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity
Jikai Jin, Vasilis Syrgkanis
We study causal representation learning, the task of recovering high-level latent variables and their causal relationships in the form of a causal graph from low-level observed dat…
cs.LG2023★ 1 cited
Understanding Incremental Learning of Gradient Descent: A Fine-grained Analysis of Matrix Sensing
Jikai Jin, Zhiyuan Li, Kaifeng Lyu +2
It is believed that Gradient Descent (GD) induces an implicit bias towards good generalization in training machine learning models. This paper provides a fine-grained analysis of t…