8 citations · 9 across the 5 of their papers we have counts for
5 papers
Robust Layerwise Scaling Rules by Proper Weight Decay Tuning
Zhiyuan Fan, Yifeng Liu, Qingyue Zhao +2
Empirical scaling laws prescribe how to allocate parameters, data, and compute, while maximal-update parameterization (P) enables learning-rate transfer across widths by equaliz…
Achieving Constant Regret in Linear Markov Decision Processes
Weitong Zhang, Zhiyuan Fan, Jiafan He +1
We study the constant regret guarantees in reinforcement learning (RL). Our objective is to design an algorithm that incurs only finite regret over infinite episodes with high prob…
On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits
Weitong Zhang, Jiafan He, Zhiyuan Fan +1
We study linear contextual bandits in the misspecified setting, where the expected reward function can be approximated by a linear function class up to a bounded misspecification l…
OpenFE: Automated Feature Generation with Expert-level Performance
Tianping Zhang, Zheyu Zhang, Zhiyuan Fan +5
The goal of automated feature generation is to liberate machine learning experts from the laborious task of manual feature generation, which is crucial for improving the learning p…
Efficient Algorithms for Sparse Moment Problems without Separation
Zhiyuan Fan, Jian Li
We consider the sparse moment problem of learning a -spike mixture in high-dimensional space from its noisy moment information in any dimension. We measure the accuracy of the l…