Baihe Huang
13 papers · 2021–2025 · 6 venues · across top CS/AI venues
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Achievements
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π Interdisciplinary Bridge Β· Bronze πΊοΈ Taxonomy Completionist (35) π Conference Polyglot Β· Silver π£ Hot Topic Early Bird ποΈ Keyword Collector (70)
π
Renaissance Researcher
(5)
π₯
Unstoppable Β· Bronze
β‘
Prolific Year Β· Productive
π
Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(10)
Optimization & Theory
(9)
Artificial Intelligence
(4)
Deep Learning
(4)
Mathematics & Optimization
(4)
Learning Types Β· Machine Learning
(4)
Optimization
(4)
Reinforcement Learning
(3)
Core AI
(3)
Learning Types Β· Deep Learning
(3)
Methods
(3)
Models
(3)
Computer Vision
(1)
Natural Language Processing
(1)
Analysis
(1)
Keywords
sample complexity
(5)
zeroth-order optimization
(3)
gradient descent
(2)
stochastic optimization
(2)
large language model
(2)
sample efficiency
(1)
image segmentation
(1)
deep reinforcement learning
(1)
function approximation
(1)
non-convex optimization
(1)
logical reasoning
(1)
convergence analysis
(1)
reinforcement learning
(1)
data valuation
(1)
markov decision process
(1)
online learning
(1)
reinforcement learning from human feedback
(1)
model alignment
(1)
label smoothing
(1)
offline reinforcement learning
(1)
Papers
Sounding that Object: Interactive Object-Aware Image to Audio Generation
ICML 2025
Data Acquisition via Experimental Design for Data Markets
NeurIPS 2024
Enhancing Language Model Alignment: A Confidence-Based Approach to Label Smoothing
EMNLP 2024
On Representation Complexity of Model-based and Model-free Reinforcement Learning
ICLR 2024
Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity
NeurIPS 2024
Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics
NeurIPS 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
NeurIPS 2023
Offline Reinforcement Learning with Realizability and Single-policy Concentrability
COLT 2022
Towards General Function Approximation in Zero-Sum Markov Games
ICLR 2022
FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis
ICML 2021
Going Beyond Linear RL: Sample Efficient Neural Function Approximation
NeurIPS 2021
Optimal Gradient-based Algorithms for Non-concave Bandit Optimization
NeurIPS 2021