Wai, Hoi-To

28 publications

ICML 2025 Clipped SGD Algorithms for Performative Prediction: Tight Bounds for Stochastic Bias and Remedies Qiang Li, Michal Yemini, Hoi To Wai

ICML 2025 RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models Quan Wei, Chung-Yiu Yau, Hoi To Wai, Yang Zhao, Dongyeop Kang, Youngsuk Park, Mingyi Hong

ICML 2024 EMC$^2$: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence Chung-Yiu Yau, Hoi To Wai, Parameswaran Raman, Soumajyoti Sarkar, Mingyi Hong

NeurIPS 2024 Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT for LLM Alignment Jiaxiang Li, Siliang Zeng, Hoi-To Wai, Chenliang Li, Alfredo Garcia, Mingyi Hong

ICMLW 2024 Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT for LLM Alignment Jiaxiang Li, Siliang Zeng, Hoi To Wai, Chenliang Li, Alfredo Garcia, Mingyi Hong

NeurIPS 2024 Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss Qiang Li, Hoi-To Wai

ICML 2024 Two-Timescale Derivative Free Optimization for Performative Prediction with Markovian Data Haitong Liu, Qiang Li, Hoi To Wai

TMLR 2023 DoCoM: Compressed Decentralized Optimization with Near-Optimal Sample Complexity Chung-Yiu Yau, Hoi To Wai

AISTATS 2023 Incremental Aggregated Riemannian Gradient Method for Distributed PCA Xiaolu Wang, Yuchen Jiao, Hoi-To Wai, Yuantao Gu

ICML 2023 Network Effects in Performative Prediction Games Xiaolu Wang, Chung-Yiu Yau, Hoi To Wai

AISTATS 2022 State Dependent Performative Prediction with Stochastic Approximation Qiang Li, Hoi-To Wai

ICLR 2022 Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach Prashant Khanduri, Haibo Yang, Mingyi Hong, Jia Liu, Hoi To Wai, Sijia Liu

NeurIPS 2022 Distributed Optimization for Overparameterized Problems: Achieving Optimal Dimension Independent Communication Complexity Bingqing Song, Ioannis Tsaknakis, Chung-Yiu Yau, Hoi-To Wai, Mingyi Hong

NeurIPS 2022 Inducing Equilibria via Incentives: Simultaneous Design-and-Play Ensures Global Convergence Boyi Liu, Jiayang Li, Zhuoran Yang, Hoi-To Wai, Mingyi Hong, Yu Nie, Zhaoran Wang

ALT 2022 Minimization by Incremental Stochastic Surrogate Optimization for Large Scale Nonconvex Problems Belhal Karimi, Hoi-To Wai, Eric Moulines, Ping Li

NeurIPS 2022 Multi-Agent Performative Prediction with Greedy Deployment and Consensus Seeking Agents Qiang Li, Chung-Yiu Yau, Hoi-To Wai

NeurIPS 2021 A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum Prashant Khanduri, Siliang Zeng, Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang

AAAI 2021 Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models Ruiyuan Wu, Anna Scaglione, Hoi-To Wai, Nurullah Karakoç, Kari Hreinsson, Wing-Kin Ma

COLT 2021 On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Hoi-To Wai

NeurIPS 2021 Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Kevin Scaman, Hoi-To Wai

NeurIPS 2020 A Stochastic Path Integral Differential EstimatoR Expectation Maximization Algorithm Gersende Fort, Eric Moulines, Hoi-To Wai

COLT 2020 Finite Time Analysis of Linear Two-Timescale Stochastic Approximation with Markovian Noise Maxim Kaledin, Eric Moulines, Alexey Naumov, Vladislav Tadic, Hoi-To Wai

NeurIPS 2020 Provably Efficient Neural GTD for Off-Policy Learning Hoi-To Wai, Zhuoran Yang, Zhaoran Wang, Mingyi Hong

COLT 2019 Non-Asymptotic Analysis of Biased Stochastic Approximation Scheme Belhal Karimi, Blazej Miasojedow, Eric Moulines, Hoi-To Wai

NeurIPS 2019 On the Global Convergence of (Fast) Incremental Expectation Maximization Methods Belhal Karimi, Hoi-To Wai, Eric Moulines, Marc Lavielle

NeurIPS 2019 Variance Reduced Policy Evaluation with Smooth Function Approximation Hoi-To Wai, Mingyi Hong, Zhuoran Yang, Zhaoran Wang, Kexin Tang

NeurIPS 2018 Low-Rank Interaction with Sparse Additive Effects Model for Large Data Frames Geneviève Robin, Hoi-To Wai, Julie Josse, Olga Klopp, Eric Moulines

NeurIPS 2018 Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization Hoi-To Wai, Zhuoran Yang, Zhaoran Wang, Mingyi Hong