Lei Ying
21 papers · 2019–2026 · 7 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.
Achievements
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🗺️ Taxonomy Completionist (32) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
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Grand Slam
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Prolific Year · Productive
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Unstoppable · Bronze
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Century Club · Bronze
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Renaissance Researcher
(7)
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Keyword Collector
(108)
Top co-authors
Research topics
Machine Learning
(18)
Learning Types
(14)
Optimization & Theory
(12)
Mathematics & Optimization
(10)
Reinforcement Learning
(9)
Methods
(9)
Optimization
(9)
Artificial Intelligence
(6)
Core AI
(6)
Applications
(3)
Mathematics
(2)
Computer Science
(1)
Deep Learning
(1)
Healthcare & Medicine
(1)
Natural Language Processing
(1)
Keywords
regret bound
(6)
constraint violation
(4)
constrained mdp
(3)
reinforcement learning
(3)
stochastic approximation
(3)
policy gradient
(3)
linear function approximation
(3)
constrained markov decision process
(3)
model-free algorithm
(2)
optimal stopping
(2)
sublinear regret
(2)
online algorithm
(2)
model-free reinforcement learning
(2)
finite-time bound
(2)
multi-armed bandit
(2)
online convex optimization
(2)
upper confidence bound
(2)
exploration-exploitation tradeoff
(2)
mean square error
(2)
network alignment
(1)
Papers
Diffusion-Network Alignment: An Efficient Algorithm and Explicit Probability Bounds
COLT 2026
Zeroth-Order Policy Gradient for Reinforcement Learning from Human Feedback without Reward Inference
ICLR 2025
Deep Reinforcement Learning for Early Diagnosis of Lung Cancer
AAAI 2024
Exploration, Exploitation, and Engagement in Multi-Armed Bandits with Abandonment
JMLR 2024
Graph Mixup on Approximate Gromov–Wasserstein Geodesics
ICML 2024
Safe Reinforcement Learning with Instantaneous Constraints: The Role of Aggressive Exploration
AAAI 2024
Fast and Regret Optimal Best Arm Identification: Fundamental Limits and Low-Complexity Algorithms
NeurIPS 2023
Learning While Scheduling in Multi-Server Systems With Unknown Statistics: MaxWeight with Discounted UCB
AISTATS 2023
Online Nonstochastic Control with Adversarial and Static Constraints
ICML 2023
On the Global Convergence of Risk-Averse Policy Gradient Methods with Expected Conditional Risk Measures
ICML 2023
Provably Efficient Model-Free Algorithms for Non-stationary CMDPs
AISTATS 2023
Sample Efficient Reinforcement Learning in Mixed Systems through Augmented Samples and Its Applications to Queueing Networks
NeurIPS 2023
A Provably-Efficient Model-Free Algorithm for Infinite-Horizon Average-Reward Constrained Markov Decision Processes
AAAI 2022
Batch Active Learning with Graph Neural Networks via Multi-Agent Deep Reinforcement Learning
AAAI 2022
Online Convex Optimization with Hard Constraints: Towards the Best of Two Worlds and Beyond
NeurIPS 2022
Triple-Q: A Model-Free Algorithm for Constrained Reinforcement Learning with Sublinear Regret and Zero Constraint Violation
AISTATS 2022
Will Bilevel Optimizers Benefit from Loops
NeurIPS 2022
An Efficient Pessimistic-Optimistic Algorithm for Stochastic Linear Bandits with General Constraints
NeurIPS 2021
The Mean-Squared Error of Double Q-Learning
NeurIPS 2020
Finite-Time Error Bounds For Linear Stochastic Approximation andTD Learning
COLT 2019
Finite-Time Performance Bounds and Adaptive Learning Rate Selection for Two Time-Scale Reinforcement Learning
NeurIPS 2019