Tianyuan Jin
14 papers · 2019–2026 · 6 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (21) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π¬
Deep Specialist
(10)
π
Grand Slam
π
Keyword Champion
(2)
π₯
Unstoppable Β· Bronze
ποΈ
Keyword Collector
(55)
π
Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(14)
Optimization & Theory
(13)
Learning Types
(11)
Mathematics & Optimization
(9)
Optimization
(9)
Artificial Intelligence
(5)
Bayesian & Probabilistic Β· Artificial Intelligence
(4)
Core AI
(2)
Reinforcement Learning
(1)
Bayesian & Probabilistic Β· Machine Learning
(1)
Core Methods
(1)
Methods
(1)
Keywords
multi-armed bandit
(11)
regret bound
(7)
thompson sampling
(5)
sample complexity
(3)
batch complexity
(3)
best arm identification
(3)
linear bandit
(3)
minimax optimality
(2)
regret minimization
(2)
asymptotic optimality
(2)
round complexity
(2)
bayesian inference
(2)
posterior sampling
(2)
bayesian optimization
(1)
query complexity
(1)
pac learning
(1)
exponential families
(1)
exponential family
(1)
bayesian learning
(1)
posterior distribution
(1)
Papers
Avoiding exp($k^*$) Scaling for Thompson Sampling in Combinatorial Semi-Bandits: From Multiple Seeds to a Single Seed
COLT 2026
Best Arm Identification with Minimal Regret
JMLR 2026
Breaking the $\log(1/\Delta_2)$ Barrier: Better Batched Best Arm Identification with Adaptive Grids
ICLR 2025
Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs
AAAI 2024
Optimal Batched Best Arm Identification
NeurIPS 2024
Optimal Batched Linear Bandits
ICML 2024
Sparsity-Agnostic Linear Bandits with Adaptive Adversaries
NeurIPS 2024
Thompson Sampling with Less Exploration is Fast and Optimal
ICML 2023
Finite-Time Regret of Thompson Sampling Algorithms for Exponential Family Multi-Armed Bandits
NeurIPS 2022
Almost Optimal Anytime Algorithm for Batched Multi-Armed Bandits
ICML 2021
Double Explore-then-Commit: Asymptotic Optimality and Beyond
COLT 2021
MOTS: Minimax Optimal Thompson Sampling
ICML 2021
Optimal Streaming Algorithms for Multi-Armed Bandits
ICML 2021
Efficient Pure Exploration in Adaptive Round model
NeurIPS 2019