Baihe Huang
13 papers · 2021–2025 · 6 conferences · across top CS/AI conferences
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(13)
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(5)
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Prolific Year
(5)
Conferences
NIPS (6)
ICLR (2)
ICML (2)
AISTATS (1)
COLT (1)
EMNLP (1)
Top co-authors
Keywords
sample complexity
(3)
zeroth-order optimization
(3)
large language model
(2)
stochastic optimization
(2)
gradient descent
(2)
offline reinforcement learning
(1)
sample efficiency
(1)
deep reinforcement learning
(1)
convergence analysis
(1)
logical reasoning
(1)
reinforcement learning
(1)
data valuation
(1)
label smoothing
(1)
reinforcement learning from human feedback
(1)
experimental design
(1)
non-convex optimization
(1)
model alignment
(1)
strongly convex
(1)
primal-dual algorithm
(1)
online learning
(1)
Papers
Sounding that Object: Interactive Object-Aware Image to Audio Generation
ICML 2025
On Representation Complexity of Model-based and Model-free Reinforcement Learning
ICLR 2024
Enhancing Language Model Alignment: A Confidence-Based Approach to Label Smoothing
EMNLP 2024
Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics
NIPS 2024
Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity
NIPS 2024
Data Acquisition via Experimental Design for Data Markets
NIPS 2024
Optimal Sample Complexity Bounds for Non-convex Optimization under Kurdyka-Lojasiewicz Condition
AISTATS 2023
Sample Complexity for Quadratic Bandits: Hessian Dependent Bounds and Optimal Algorithms
NIPS 2023
Offline Reinforcement Learning with Realizability and Single-policy Concentrability
COLT 2022
Towards General Function Approximation in Zero-Sum Markov Games
ICLR 2022
Going Beyond Linear RL: Sample Efficient Neural Function Approximation
NIPS 2021
FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis
ICML 2021
Optimal Gradient-based Algorithms for Non-concave Bandit Optimization
NIPS 2021