26 citations · 104 across the 21 of their papers we have counts for
32 papers
Product Graph Learning from Multi-attribute Graph Signals with Inter-layer Coupling
Chenyue Zhang, Yiran He, Hoi-To Wai
This paper considers learning a product graph from multi-attribute graph signals. Our work is motivated by the widespread presence of multilayer networks that feature interactions…
Multi-agent Performative Prediction with Greedy Deployment and Consensus Seeking Agents
Qiang Li, Chung-Yiu Yau, Hoi-To Wai
We consider a scenario where multiple agents are learning a common decision vector from data which can be influenced by the agents' decisions. This leads to the problem of multi-ag…
On the Stability of Low Pass Graph Filter With a Large Number of Edge Rewires
Hoang-Son Nguyen, Yiran He, Hoi-To Wai
Recently, the stability of graph filters has been studied as one of the key theoretical properties driving the highly successful graph convolutional neural networks (GCNs). The sta…
An Empirical Study on Compressed Decentralized Stochastic Gradient Algorithms with Overparameterized Models
Arjun Ashok Rao, Hoi-To Wai
This paper considers decentralized optimization with application to machine learning on graphs. The growing size of neural network (NN) models has motivated prior works on decentra…
State Dependent Performative Prediction with Stochastic Approximation
Qiang Li, Hoi-To Wai
This paper studies the performative prediction problem which optimizes a stochastic loss function with data distribution that depends on the decision variable. We consider a settin…
Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize
Alain Durmus, Eric Moulines, Alexey Naumov +3
This paper provides a non-asymptotic analysis of linear stochastic approximation (LSA) algorithms with fixed stepsize. This family of methods arises in many machine learning tasks…