Hoi-To Wai

ORCID

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 123

Top Venues

CoRR

ICASSP

IEEE Trans. Signal Process.

NeurIPS

Arizona State University, Tempe, USA (PHD)

Education History

Arizona State University, Tempe, USA

PHD

Publications

Hang Liu, Anna Scaglione, Hoi-To Wai
Blind Graph Matching Using Graph Signals. IEEE Trans. Signal Process. 72 (2024)
Qiang Li, Michal Yemini, Hoi-To Wai
Clipped SGD Algorithms for Privacy Preserving Performative Prediction: Bias Amplification and Remedies. CoRR (2024)
Xiaolu Wang, Yuchang Sun, Hoi-To Wai, Jun Zhang
Dual-Delayed Asynchronous SGD for Arbitrarily Heterogeneous Data. CoRR (2024)
Jiaxiang Li, Siliang Zeng, Hoi-To Wai, Chenliang Li, Alfredo García, Mingyi Hong
Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT for LLM Alignment. CoRR (2024)
Jiamin Cai, Chenyue Zhang, Hoi-To Wai
Optimal Pricing for Linear-Quadratic Games with Nonlinear Interaction Between Agents. CoRR (2024)
Chenyue Zhang, Yiran He, Hoi-To Wai
Detecting Low Pass Graph Signals via Spectral Pattern: Sampling Complexity and Applications. IEEE Trans. Signal Process. 72 (2024)
Chenyue Zhang, Hoi-To Wai
Learning Multiplex Graph With Inter-Layer Coupling. ICASSP (2024)
Chung-Yiu Yau, Hoi-To Wai, Parameswaran Raman, Soumajyoti Sarkar, Mingyi Hong
: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence. CoRR (2024)
Jiamin Cai, Chenyue Zhang, Hoi-To Wai
Optimal Pricing for Linear-Quadratic Games With Nonlinear Interaction Between Agents. IEEE Control. Syst. Lett. 8 (2024)
Chung-Yiu Yau, Hoi-To Wai
DoCoM: Compressed Decentralized Optimization with Near-Optimal Sample Complexity. Trans. Mach. Learn. Res. 2023 (2023)
Xiaolu Wang, Chung-Yiu Yau, Hoi-To Wai
Network Effects in Performative Prediction Games. ICML (2023)
Xiaolu Wang, Yuchen Jiao, Hoi-To Wai, Yuantao Gu
Incremental Aggregated Riemannian Gradient Method for Distributed PCA. AISTATS (2023)
Sharon Gannot, Zheng-Hua Tan, Martin Haardt, Nancy F. Chen, Hoi-To Wai, Ivan Tashev, Walter Kellermann, Justin Dauwels
Data Science Education: The Signal Processing Perspective [SP Education]. IEEE Signal Process. Mag. 40 (7) (2023)
Wai-Yiu Keung, Hoi-To Wai, Wing-Kin Ma
Secure Integrated Sensing and Communication Downlink Beamforming: A Semidefinite Relaxation Approach With Tightness Guaranteed. ICASSP Workshops (2023)
Aymeric Dieuleveut, Gersende Fort, Eric Moulines, Hoi-To Wai
Stochastic Approximation Beyond Gradient for Signal Processing and Machine Learning. IEEE Trans. Signal Process. 71 (2023)
Yiran He, Hoi-To Wai
Central Nodes Detection from Partially Observed Graph Signals. ICASSP (2023)
Xiaolu Wang, Cheng Jin, Hoi-To Wai, Yuantao Gu
Linear Speedup of Incremental Aggregated Gradient Methods on Streaming Data. CoRR (2023)
Katsuki Fukumoto, Koki Yamada, Yuichi Tanaka, Hoi-To Wai
Clustering of Time-Varying Graphs Based on Temporal Label Smoothness. CoRR (2023)
Hang Liu, Anna Scaglione, Hoi-To Wai
Solutions of the Graph Matching Problem Using Graph Signals. CAMSAP (2023)
Xiaolu Wang, Cheng Jin, Hoi-To Wai, Yuantao Gu
Linear Speedup of Incremental Aggregated Gradient Methods on Streaming Data. CDC (2023)
Chenyue Zhang, Yiran He, Hoi-To Wai
Product Graph Learning From Multi-Attribute Graph Signals with Inter-Layer Coupling. ICASSP (2023)
Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang
A Two-Timescale Stochastic Algorithm Framework for Bilevel Optimization: Complexity Analysis and Application to Actor-Critic. SIAM J. Optim. 33 (1) (2023)
Chung-Yiu Yau, Hoi-To Wai
Fully Stochastic Distributed Convex Optimization on Time-Varying Graph with Compression. CDC (2023)
Prashant Khanduri, Haibo Yang, Mingyi Hong, Jia Liu, Hoi-To Wai, Sijia Liu
Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach. ICLR (2022)
Qiang Li, Chung-Yiu Yau, Hoi-To Wai
Multi-agent Performative Prediction with Greedy Deployment and Consensus Seeking Agents. NeurIPS (2022)
Berkay Turan, César A. Uribe, Hoi-To Wai, Mahnoosh Alizadeh
Robust Distributed Optimization With Randomly Corrupted Gradients. IEEE Trans. Signal Process. 70 (2022)
Hoi-To Wai, Yonina C. Eldar, Asuman E. Ozdaglar, Anna Scaglione
Community Inference From Partially Observed Graph Signals: Algorithms and Analysis. IEEE Trans. Signal Process. 70 (2022)
Yan Huang, Jinming Xu, Wenchao Meng, Hoi-To Wai
Stochastic Gradient Tracking Methods for Distributed Personalized Optimization over Networks. CDC (2022)
Yiran He, Hoi-To Wai
Online Inference for Mixture Model of Streaming Graph Signals With Sparse Excitation. IEEE Trans. Signal Process. 70 (2022)
Qiang Li, Hoi-To Wai
On the Role of Data Homogeneity in Multi-Agent Non-convex Stochastic Optimization. CDC (2022)
Belhal Karimi, Hoi-To Wai, Eric Moulines, Ping Li
Minimization by Incremental Stochastic Surrogate Optimization for Large Scale Nonconvex Problems. ALT (2022)
Yiran He, Hoi-To Wai
Detecting Central Nodes From Low-Rank Excited Graph Signals via Structured Factor Analysis. IEEE Trans. Signal Process. 70 (2022)
Hoang-Son Nguyen, Yiran He, Hoi-To Wai
On the Stability of Low Pass Graph Filter with a Large Number of Edge Rewires. ICASSP (2022)
Boyi Liu, Jiayang Li, Zhuoran Yang, Hoi-To Wai, Mingyi Hong, Yu Nie, Zhaoran Wang
Inducing Equilibria via Incentives: Simultaneous Design-and-Play Ensures Global Convergence. NeurIPS (2022)
Bingqing Song, Ioannis C. Tsaknakis, Chung-Yiu Yau, Hoi-To Wai, Mingyi Hong
Distributed Optimization for Overparameterized Problems: Achieving Optimal Dimension Independent Communication Complexity. NeurIPS (2022)
Yiran He, Hoi-To Wai
Joint Centrality Estimation and Graph Identification from Mixture of Low Pass Graph Signals. ICASSP (2022)
Chung-Yiu Yau, Hoi-To Wai
DoCoM-SGT: Doubly Compressed Momentum-assisted Stochastic Gradient Tracking Algorithm for Communication Efficient Decentralized Learning. CoRR (2022)
Qiang Li, Hoi-To Wai
State Dependent Performative Prediction with Stochastic Approximation. AISTATS (2022)
Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Kevin Scaman, Hoi-To Wai
Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize. NeurIPS (2021)
Arjun Ashok Rao, Hoi-To Wai
An Empirical Study on Compressed Decentralized Stochastic Gradient Algorithms with Overparameterized Models. CoRR (2021)
Yiran He, Hoi-To Wai
Provably Fast Asynchronous And Distributed Algorithms For Pagerank Centrality Computation. ICASSP (2021)
Berkay Turan, César A. Uribe, Hoi-To Wai, Mahnoosh Alizadeh
On Robustness of the Normalized Subgradient Method with Randomly Corrupted Subgradients. ACC (2021)
Ruiyuan Wu, Anna Scaglione, Hoi-To Wai, Nurullah Karakoç, Kari Hreinsson, Wing-Kin Ma
Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models. AAAI (2021)
Berkay Turan, César A. Uribe, Hoi-To Wai, Mahnoosh Alizadeh
Resilient Primal-Dual Optimization Algorithms for Distributed Resource Allocation. IEEE Trans. Control. Netw. Syst. 8 (1) (2021)
Gersende Fort, Eric Moulines, Hoi-To Wai
Geom-Spider-EM: Faster Variance Reduced Stochastic Expectation Maximization for Nonconvex Finite-Sum Optimization. ICASSP (2021)
Prashant Khanduri, Siliang Zeng, Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang
A Momentum-Assisted Single-Timescale Stochastic Approximation Algorithm for Bilevel Optimization. CoRR (2021)
Yiran He, Hoi-To Wai
Identifying First-Order Lowpass Graph Signals Using Perron Frobenius Theorem. ICASSP (2021)
Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Kevin Scaman, Hoi-To Wai
Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize. CoRR (2021)
Arjun Ashok Rao, Hoi-To Wai
An Empirical Study on Compressed Decentralized Stochastic Gradient Algorithms with Overparameterized Models. APSIPA ASC (2021)
Berkay Turan, César A. Uribe, Hoi-To Wai, Mahnoosh Alizadeh
On Robustness of the Normalized Random Block Coordinate Method for Non-Convex Optimization. CDC (2021)
Hoang-Son Nguyen, Yiran He, Hoi-To Wai
On the Stability of Low Pass Graph Filter With a Large Number of Edge Rewires. CoRR (2021)
Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Hoi-To Wai
On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning. COLT (2021)
Prashant Khanduri, Siliang Zeng, Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang
A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum. NeurIPS (2021)
Berkay Turan, Cesar A. Uribe, Hoi-To Wai, Mahnoosh Alizadeh
Robust Distributed Optimization With Randomly Corrupted Gradients. CoRR (2021)
Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Hoi-To Wai
On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning. CoRR (2021)
Boyi Liu, Jiayang Li, Zhuoran Yang, Hoi-To Wai, Mingyi Hong, Yu Marco Nie, Zhaoran Wang
Inducing Equilibria via Incentives: Simultaneous Design-and-Play Finds Global Optima. CoRR (2021)
Berkay Turan, Cesar A. Uribe, Hoi-To Wai, Mahnoosh Alizadeh
Resilient Primal-Dual Optimization Algorithms for Distributed Resource Allocation. CoRR (2020)
Maxim Kaledin, Eric Moulines, Alexey Naumov, Vladislav Tadic, Hoi-To Wai
Finite Time Analysis of Linear Two-timescale Stochastic Approximation with Markovian Noise. CoRR (2020)
Hoi-To Wai, Zhuoran Yang, Zhaoran Wang, Mingyi Hong
Provably Efficient Neural GTD for Off-Policy Learning. NeurIPS (2020)
Maxim Kaledin, Eric Moulines, Alexey Naumov, Vladislav Tadic, Hoi-To Wai
Finite Time Analysis of Linear Two-timescale Stochastic Approximation with Markovian Noise. COLT (2020)
Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang
A Two-Timescale Framework for Bilevel Optimization: Complexity Analysis and Application to Actor-Critic. CoRR (2020)
Tsung-Hui Chang, Mingyi Hong, Hoi-To Wai, Xinwei Zhang, Songtao Lu
Distributed Learning in the Nonconvex World: From batch data to streaming and beyond. IEEE Signal Process. Mag. 37 (3) (2020)
Hoi-To Wai, Santiago Segarra, Asuman E. Ozdaglar, Anna Scaglione, Ali Jadbabaie
Blind Community Detection From Low-Rank Excitations of a Graph Filter. IEEE Trans. Signal Process. 68 (2020)
Gersende Fort, Eric Moulines, Hoi-To Wai
Geom-SPIDER-EM: Faster Variance Reduced Stochastic Expectation Maximization for Nonconvex Finite-Sum Optimization. CoRR (2020)
Hoi-To Wai, Wei Shi, César A. Uribe, Angelia Nedic, Anna Scaglione
Accelerating incremental gradient optimization with curvature information. Comput. Optim. Appl. 76 (2) (2020)
Gersende Fort, Eric Moulines, Hoi-To Wai
A Stochastic Path-Integrated Differential EstimatoR Expectation Maximization Algorithm. CoRR (2020)
Raksha Ramakrishna, Hoi-To Wai, Anna Scaglione
A User Guide to Low-Pass Graph Signal Processing and Its Applications: Tools and Applications. IEEE Signal Process. Mag. 37 (6) (2020)
Xiao Fu, Shahana Ibrahim, Hoi-To Wai, Cheng Gao, Kejun Huang
Block-Randomized Stochastic Proximal Gradient for Low-Rank Tensor Factorization. IEEE Trans. Signal Process. 68 (2020)
Yiran He, Hoi-To Wai
Estimating Centrality Blindly From Low-Pass Filtered Graph Signals. ICASSP (2020)
Alain Durmus, Pablo Jiménez, Éric Moulines, Salem Said, Hoi-To Wai
Convergence Analysis of Riemannian Stochastic Approximation Schemes. CoRR (2020)
T. Mitchell Roddenberry, Michael T. Schaub, Hoi-To Wai, Santiago Segarra
Exact Blind Community Detection from Signals on Multiple Graphs. CoRR (2020)
Ruiyuan Wu, Hoi-To Wai, Wing-Kin Ma
Hybrid Inexact BCD for Coupled Structured Matrix Factorization in Hyperspectral Super-Resolution. IEEE Trans. Signal Process. 68 (2020)
Hoi-To Wai
On the Convergence of Consensus Algorithms with Markovian noise and Gradient Bias. CDC (2020)
Gersende Fort, Eric Moulines, Hoi-To Wai
A Stochastic Path Integral Differential EstimatoR Expectation Maximization Algorithm. NeurIPS (2020)
Tsung-Hui Chang, Mingyi Hong, Hoi-To Wai, Xinwei Zhang, Songtao Lu
Distributed Learning in the Non-Convex World: From Batch to Streaming Data, and Beyond. CoRR (2020)
T. Mitchell Roddenberry, Michael T. Schaub, Hoi-To Wai, Santiago Segarra
Exact Blind Community Detection From Signals on Multiple Graphs. IEEE Trans. Signal Process. 68 (2020)
Ruiyuan Wu, Anna Scaglione, Hoi-To Wai, Nurullah Karakoç, Kari Hreinsson, Wing-Kin Ma
Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models. CoRR (2020)
Hoi-To Wai, Yonina C. Eldar, Asuman E. Ozdaglar, Anna Scaglione
Community Inference from Graph Signals with Hidden Nodes. ICASSP (2019)
Michael T. Schaub, Santiago Segarra, Hoi-To Wai
Spectral partitioning of time-varying networks with unobserved edges. CoRR (2019)
Mahnoosh Alizadeh, Hoi-To Wai, Andrea Goldsmith, Anna Scaglione
Retail and Wholesale Electricity Pricing Considering Electric Vehicle Mobility. IEEE Trans. Control. Netw. Syst. 6 (1) (2019)
Belhal Karimi, Hoi-To Wai, Eric Moulines, Marc Lavielle
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods. NeurIPS (2019)
Belhal Karimi, Blazej Miasojedow, Eric Moulines, Hoi-To Wai
Non-asymptotic Analysis of Biased Stochastic Approximation Scheme. COLT (2019)
Belhal Karimi, Hoi-To Wai, Eric Moulines, Marc Lavielle
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods. CoRR (2019)
Hoi-To Wai, Mingyi Hong, Zhuoran Yang, Zhaoran Wang, Kexin Tang
Variance Reduced Policy Evaluation with Smooth Function Approximation. NeurIPS (2019)
Belhal Karimi, Blazej Miasojedow, Eric Moulines, Hoi-To Wai
Non-asymptotic Analysis of Biased Stochastic Approximation Scheme. CoRR (2019)
Hoi-To Wai, Anna Scaglione, Baruch Barzel, Amir Leshem
Joint Network Topology and Dynamics Recovery From Perturbed Stationary Points. IEEE Trans. Signal Process. 67 (17) (2019)
Xiao Fu, Cheng Gao, Hoi-To Wai, Kejun Huang
Block-Randomized Stochastic Proximal Gradient for Low-Rank Tensor Factorization. CoRR (2019)
César A. Uribe, Hoi-To Wai, Mahnoosh Alizadeh
Resilient Distributed Optimization Algorithms for Resource Allocation. CDC (2019)
Michael T. Schaub, Santiago Segarra, Hoi-To Wai
Spectral Partitioning of Time-varying Networks with Unobserved Edges. ICASSP (2019)
Xiao Fu, Cheng Gao, Hoi-To Wai, Kejun Huang
Block-randomized Stochastic Proximal Gradient for Constrained Low-rank Tensor Factorization. ICASSP (2019)
Sissi Xiaoxiao Wu, Hoi-To Wai, Lin Li, Anna Scaglione
A Review of Distributed Algorithms for Principal Component Analysis. Proc. IEEE 106 (8) (2018)
Hoi-To Wai, Santiago Segarra, Asuman E. Ozdaglar, Anna Scaglione, Ali Jadbabaie
Community Detection from Low-Rank Excitations of a Graph Filter. ICASSP (2018)
Hoi-To Wai, Zhuoran Yang, Zhaoran Wang, Mingyi Hong
Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization. NeurIPS (2018)
Geneviève Robin, Hoi-To Wai, Julie Josse, Olga Klopp, Eric Moulines
Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames. NeurIPS (2018)
Hoi-To Wai, Anna Scaglione, Baruch Barzel, Amir Leshem
Network Inference from Complex Systems Steady States Observations: Theory and Methods. DSW (2018)
Nikhil Ravi, Raksha Ramakrishna, Hoi-To Wai, Anna Scaglione
Network Inference and its Application to the Estimation of Crowd Dynamics from IoT Sensors. SPAWC (2018)
Hoi-To Wai, Nikolaos M. Freris, Angelia Nedic, Anna Scaglione
SUCAG: Stochastic Unbiased Curvature-aided Gradient Method for Distributed Optimization. CDC (2018)
Ruiyuan Wu, Chun-Hei Chan, Hoi-To Wai, Wing-Kin Ma, Xiao Fu
Hi, Bcd! Hybrid Inexact Block Coordinate Descent for Hyperspectral Super-Resolution. ICASSP (2018)
Hoi-To Wai, Asuman E. Ozdaglar, Anna Scaglione
Identifying Susceptible Agents in Time Varying Opinion Dynamics Through Compressive Measurements. ICASSP (2018)
Sissi Xiaoxiao Wu, Hoi-To Wai, Anna Scaglione, Angelia Nedic, Amir Leshem
Data Injection Attack on Decentralized Optimization. ICASSP (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Hoi-To Wai