Yinyu Ye
23 papers · 2017–2025 · 8 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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πΊοΈ Taxonomy Completionist (42) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Grand Slam
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Trend Setter
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The Questioner
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Keyword Collector
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Century Club Β· Bronze
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Research topics
Machine Learning
(20)
Mathematics & Optimization
(20)
Optimization
(19)
Optimization & Theory Β· Machine Learning
(19)
Learning Types
(6)
Reinforcement Learning
(5)
Deep Learning
(4)
Artificial Intelligence
(3)
Core AI
(3)
Methods
(3)
Applications
(2)
Mathematics
(2)
Optimization & Theory Β· Deep Learning
(2)
Natural Language Processing
(1)
Architectures
(1)
Keywords
linear programming
(4)
sample complexity
(4)
online linear programming
(3)
reinforcement learning
(3)
regret bound
(3)
first-order method
(3)
online learning
(3)
gradient dominance
(2)
newton method
(2)
distributionally robust optimization
(2)
sparse optimization
(2)
regret
(2)
non-convex optimization
(2)
convergence analysis
(2)
variance reduction
(2)
markov decision process
(2)
stochastic optimization
(2)
resource allocation
(2)
convergence
(2)
hypergradient descent
(2)
Papers
Adam-mini: Use Fewer Learning Rates To Gain More
ICLR 2025
Gradient Methods with Online Scaling
COLT 2025
Provable and Practical Online Learning Rate Adaptation with Hypergradient Descent
ICML 2025
Wait-Less Offline Tuning and Re-solving for Online Decision Making
ICML 2025
Achieving OΜ(1/Ξ΅) Sample Complexity for Constrained Markov Decision Process
NeurIPS 2024
A Homogenization Approach for Gradient-Dominated Stochastic Optimization
UAI 2024
A Single-Loop Robust Policy Gradient Method for Robust Markov Decision Processes
ICML 2024
Decoupling Learning and Decision-Making: Breaking the O(βT) Barrier in Online Resource Allocation with First-Order Methods
ICML 2024
Learning to Pivot as a Smart Expert
AAAI 2024
Sketched Newton Value Iteration for Large-Scale Markov Decision Processes
AAAI 2024
Trust Region Methods for Nonconvex Stochastic Optimization beyond Lipschitz Smoothness
AAAI 2024
Solving Linear Programs with Fast Online Learning Algorithms
ICML 2023
The Symmetry between Arms and Knapsacks: A Primal-Dual Approach for Bandits with Knapsacks
ICML 2021
Conic Descent and its Application to Memory-efficient Optimization over Positive Semidefinite Matrices
NeurIPS 2020
Distributionally Robust Local Non-parametric Conditional Estimation
NeurIPS 2020
Simple and Fast Algorithm for Binary Integer and Online Linear Programming
NeurIPS 2020
Solving Discounted Stochastic Two-Player Games with Near-Optimal Time and Sample Complexity
AISTATS 2020
Approximation Hardness for A Class of Sparse Optimization Problems
JMLR 2019
Interior-Point Methods Strike Back: Solving the Wasserstein Barycenter Problem
NeurIPS 2019
Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go?
ICML 2018
Learning in Games with Lossy Feedback
NeurIPS 2018
Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model
NeurIPS 2018
Strong NP-Hardness for Sparse Optimization with Concave Penalty Functions
ICML 2017