450 citations · 1.2k across the 59 of their papers we have counts for
61 papers
Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence
Yuki Takezawa, Ryoma Sato, Han Bao +2
Decentralized learning has recently been attracting increasing attention for its applications in parallel computation and privacy preservation. Many recent studies stated that the…
Nystrom Method for Accurate and Scalable Implicit Differentiation
Ryuichiro Hataya, Makoto Yamada
The essential difficulty of gradient-based bilevel optimization using implicit differentiation is to estimate the inverse Hessian vector product with respect to neural network para…
Twin Papers: A Simple Framework of Causal Inference for Citations via Coupling
Ryoma Sato, Makoto Yamada, Hisashi Kashima
The research process includes many decisions, e.g., how to entitle and where to publish the paper. In this paper, we introduce a general framework for investigating the effects of…
Approximating 1-Wasserstein Distance with Trees
Makoto Yamada, Yuki Takezawa, Ryoma Sato +3
Wasserstein distance, which measures the discrepancy between distributions, shows efficacy in various types of natural language processing (NLP) and computer vision (CV) applicatio…
Feature Selection for Discovering Distributional Treatment Effect Modifiers
Yoichi Chikahara, Makoto Yamada, Hisashi Kashima
Finding the features relevant to the difference in treatment effects is essential to unveil the underlying causal mechanisms. Existing methods seek such features by measuring how g…
Communication Compression for Decentralized Learning with Operator Splitting Methods
Yuki Takezawa, Kenta Niwa, Makoto Yamada
In decentralized learning, operator splitting methods using a primal-dual formulation (e.g., the Edge-Consensus Learning (ECL)) has been shown to be robust to heterogeneous data an…