26 citations · 136 across the 53 of their papers we have counts for
7 papers · 1 filter
Estimating Centrality Blindly from Low-pass Filtered Graph Signals
Yiran He, Hoi-To Wai
This paper considers blind methods for centrality estimation from graph signals. We model graph signals as the outcome of an unknown low-pass graph filter excited with influences g…
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods
Belhal Karimi, Hoi-To Wai, Eric Moulines +1
The EM algorithm is one of the most popular algorithm for inference in latent data models. The original formulation of the EM algorithm does not scale to large data set, because th…
Hybrid Inexact BCD for Coupled Structured Matrix Factorization in Hyperspectral Super-Resolution
Ruiyuan Wu, Hoi-To Wai, Wing-Kin Ma
This paper develops a first-order optimization method for coupled structured matrix factorization (CoSMF) problems that arise in the context of hyperspectral super-resolution (HSR)…
Spectral partitioning of time-varying networks with unobserved edges
Michael T. Schaub, Santiago Segarra, Hoi-To Wai
We discuss a variant of `blind' community detection, in which we aim to partition an unobserved network from the observation of a (dynamical) graph signal defined on the network. W…
Resilient Distributed Optimization Algorithms for Resource Allocation
Cesar A. Uribe, Hoi-To Wai, Mahnoosh Alizadeh
Distributed algorithms provide flexibility over centralized algorithms for resource allocation problems, e.g., cyber-physical systems. However, the distributed nature of these algo…
Non-asymptotic Analysis of Biased Stochastic Approximation Scheme
Belhal Karimi, Blazej Miasojedow, Eric Moulines +1
Stochastic approximation (SA) is a key method used in statistical learning. Recently, its non-asymptotic convergence analysis has been considered in many papers. However, most of t…