8 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Learning sum of diverse features: computational hardness and efficient gradient-based training for ridge combinations
Kazusato Oko, Yujin Song, Taiji Suzuki +1
We study the computational and sample complexity of learning a target function with additive structure, that is, $f_*(x) = \frac{1}{\sqrt{M}}\sum_{m…
stat.ML2023
Primal and Dual Analysis of Entropic Fictitious Play for Finite-sum Problems
Atsushi Nitanda, Kazusato Oko, Denny Wu +2
The entropic fictitious play (EFP) is a recently proposed algorithm that minimizes the sum of a convex functional and entropy in the space of measures -- such an objective naturall…
stat.ML2023★ 8 cited
Diffusion Models are Minimax Optimal Distribution Estimators
Kazusato Oko, Shunta Akiyama, Taiji Suzuki
While efficient distribution learning is no doubt behind the groundbreaking success of diffusion modeling, its theoretical guarantees are quite limited. In this paper, we provide t…