Go to Header
Go to Navigation
Go to Content
Go to Footer
Login
Help
中文（繁體）
Research Resources
CUHK UPDates
Theses
Experts List
User Guides
About Us
List of Researchers
> Associate Professor Hoi To WAI
Home
Research Outputs
Researcher Profiles
Department Profiles
Research Areas
Professor WAI Hoi To
Personal Information
Position and Department
Associate Professor
,
Department of Systems Engineering and Engineering Management
ORCiD
0000-0003-4796-4483
CUHK Research Outputs
1 of 2
Learning Multiplex Graph With Inter-Layer Coupling
(
2024
)
A Two-Timescale Stochastic Algorithm Framework for Bilevel Optimization: Complexity Analysis and Application to Actor-Critic
(
2023
)
Central Nodes Detection from Partially Observed Graph Signals
(
2023
)
Data Science Education: The Signal Processing Perspective [SP Education]
(
2023
)
Incremental Aggregated Riemannian Gradient Method for Distributed PCA
(
2023
)
Network Effects in Performative Prediction Games
(
2023
)
Product Graph Learning From Multi-Attribute Graph Signals with Inter-Layer Coupling
(
2023
)
Secure Integrated Sensing and Communication Downlink Beamforming: A Semidefinite Relaxation Approach with Tightness Guaranteed
(
2023
)
Stochastic Approximation Beyond Gradient for Signal Processing and Machine Learning
(
2023
)
Community Inference From Partially Observed Graph Signals: Algorithms and Analysis
(
2022
)
Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach
(
2022
)
Detecting central nodes from low-rank excited graph signals via structured factor analysis
(
2022
)
Distributed Optimization for Overparameterized Problems: Achieving Optimal Dimension Independent Communication Complexity
(
2022
)
Inducing Equilibria via Incentives: Simultaneous Design-and-Play Ensures Global Convergence
(
2022
)
Joint Centrality Estimation and Graph Identification from Mixture of Low Pass Graph Signals
(
2022
)
Minimization by Incremental Stochastic Surrogate Optimization for Large Scale Nonconvex Problems
(
2022
)
Multi-agent Performative Prediction with Greedy Deployment and Consensus Seeking Agents
(
2022
)
Online Inference for Mixture Model of Streaming Graph Signals with Sparse Excitation
(
2022
)
On the Role of Data Homogeneity in Multi-Agent Non-convex Stochastic Optimization
(
2022
)
On the Stability of Low Pass Graph Filter with a Large Number of Edge Rewires
(
2022
)
Robust Distributed Optimization With Randomly Corrupted Gradients
(
2022
)
State Dependent Performative Prediction with Stochastic Approximation
(
2022
)
Stochastic Gradient Tracking Methods for Distributed Personalized Optimization over Networks
(
2022
)
A near-optimal algorithm for stochastic bilevel optimization via double-momentum
(
2021
)
An Empirical Study on Compressed Decentralized Stochastic Gradient Algorithms with Overparameterized Models
(
2021
)
Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models
(
2021
)
GEOM-SPIDER-EM: Faster Variance Reduced Stochastic Expectation Maximization for Nonconvex Finite-Sum Optimization
(
2021
)
Identifying First-Order Lowpass Graph Signals Using Perron Frobenius Theorem
(
2021
)
On Robustness of the Normalized Random Block Coordinate Method for Non-Convex Optimization
(
2021
)
On Robustness of the Normalized Subgradient Method with Randomly Corrupted Subgradients
(
2021
)
On the stability of random matrix product with Markovian noise: Application to linear stochastic approximation and TD learning
(
2021
)
Provably Fast Asynchronous And Distributed Algorithms For Pagerank Centrality Computation
(
2021
)
Resilient Primal-Dual Optimization Algorithms for Distributed Resource Allocation
(
2021
)
Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize
(
2021
)
Accelerating incremental gradient optimization with curvature information
(
2020
)
A Stochastic Path Integral Differential EstimatoR Expectation Maximization Algorithm
(
2020
)
A User Guide to Low-Pass Graph Signal Processing and Its Applications: Tools and Applications
(
2020
)
Blind Community Detection From Low-Rank Excitations of a Graph Filter
(
2020
)
Block-Randomized Stochastic Proximal Gradient for Low-Rank Tensor Factorization
(
2020
)
Distributed Learning in the Non-Convex World: From Batch to Streaming Data, and Beyond
(
2020
)
Estimating Centrality Blindly From Low-Pass Filtered Graph Signals
(
2020
)
Exact blind community detection from signals on multiple graphs
(
2020
)
Finite time analysis of linear two-timescale stochastic approximation with Markovian noise
(
2020
)
Hybrid Inexact BCD for Coupled Structured Matrix Factorization in Hyperspectral Super-Resolution
(
2020
)
On the Convergence of Consensus Algorithms with Markovian noise and Gradient Bias
(
2020
)
Provably Efficient Neural GTD for Off-Policy Learning
(
2020
)
Block-randomized Stochastic Proximal Gradient for Constrained Low-rank Tensor Factorization
(
2019
)
Community Inference from Graph Signals with Hidden Nodes
(
2019
)
Joint Network Topology and Dynamics Recovery from Perturbed Stationary Points
(
2019
)
Non-asymptotic Analysis of Biased Stochastic Approximation Scheme
(
2019
)
Share Link
Last updated on 2024-11-12 at 06:50
Share Link
Your name*
Your email*
Recipient's name*
Recipient's email*
Message
Auxilliary Information
No information will be stored or shared with any third party.
Cancel
Our policy towards the use of cookies
All Clarivate Analytics websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.
Ok to Continue
Cookie Policy
