257 citations · 1k across the 75 of their papers we have counts for
5 papers · 1 filter
Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames
Geneviève Robin, Hoi-To Wai, Julie Josse +2
Many applications of machine learning involve the analysis of large data frames-matrices collecting heterogeneous measurements (binary, numerical, counts, etc.) across samples-with…
Blind Community Detection from Low-rank Excitations of a Graph Filter
Hoi-To Wai, Santiago Segarra, Asuman E. Ozdaglar +2
This paper considers a new framework to detect communities in a graph from the observation of signals at its nodes. We model the observed signals as noisy outputs of an unknown net…
Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization
Hoi-To Wai, Zhuoran Yang, Zhaoran Wang +1
Despite the success of single-agent reinforcement learning, multi-agent reinforcement learning (MARL) remains challenging due to complex interactions between agents. Motivated by d…
Accelerating Incremental Gradient Optimization with Curvature Information
Hoi-To Wai, Wei Shi, Cesar A. Uribe +2
This paper studies an acceleration technique for incremental aggregated gradient ({\sf IAG}) method through the use of \emph{curvature} information for solving strongly convex fini…
SUCAG: Stochastic Unbiased Curvature-aided Gradient Method for Distributed Optimization
Hoi-To Wai, Nikolaos M. Freris, Angelia Nedic +1
We propose and analyze a new stochastic gradient method, which we call Stochastic Unbiased Curvature-aided Gradient (SUCAG), for finite sum optimization problems. SUCAG constitutes…