Hoi-To Wai
20 papers · 2018–2024 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
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Research topics
Machine Learning
(18)
Optimization & Theory Β· Machine Learning
(18)
Mathematics & Optimization
(8)
Learning Types
(8)
Optimization
(8)
Reinforcement Learning
(5)
Methods
(5)
Artificial Intelligence
(4)
Core AI
(3)
Core Methods
(3)
Deep Learning
(2)
Learning Paradigms
(2)
Bayesian & Probabilistic
(1)
Models
(1)
Optimization & Theory Β· Deep Learning
(1)
Keywords
non-convex optimization
(5)
stochastic approximation
(4)
latent variable model
(3)
stochastic optimization
(3)
markov chain
(3)
neural network
(3)
decentralized optimization
(3)
performative prediction
(3)
policy evaluation
(3)
markovian noise
(2)
bilevel optimization
(2)
convergence rate
(2)
reinforcement learning
(2)
stochastic gradient
(2)
expectation maximization
(2)
stochastic gradient descent
(2)
variance reduction
(2)
communication complexity
(2)
finite-time analysis
(2)
multi-agent system
(2)
Papers
Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT for LLM Alignment
NeurIPS 2024
Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss
NeurIPS 2024
Incremental Aggregated Riemannian Gradient Method for Distributed PCA
AISTATS 2023
Distributed Optimization for Overparameterized Problems: Achieving Optimal Dimension Independent Communication Complexity
NeurIPS 2022
Inducing Equilibria via Incentives: Simultaneous Design-and-Play Ensures Global Convergence
NeurIPS 2022
Minimization by Incremental Stochastic Surrogate Optimization for Large Scale Nonconvex Problems
ALT 2022
Multi-agent Performative Prediction with Greedy Deployment and Consensus Seeking Agents
NeurIPS 2022
State Dependent Performative Prediction with Stochastic Approximation
AISTATS 2022
A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum
NeurIPS 2021
Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models
AAAI 2021
On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning
COLT 2021
Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize
NeurIPS 2021
A Stochastic Path Integral Differential EstimatoR Expectation Maximization Algorithm
NeurIPS 2020
Finite Time Analysis of Linear Two-timescale Stochastic Approximation with Markovian Noise
COLT 2020
Provably Efficient Neural GTD for Off-Policy Learning
NeurIPS 2020
Non-asymptotic Analysis of Biased Stochastic Approximation Scheme
COLT 2019
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods
NeurIPS 2019
Variance Reduced Policy Evaluation with Smooth Function Approximation
NeurIPS 2019
Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames
NeurIPS 2018
Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization
NeurIPS 2018