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Shinji Ito

Topic trends: 32,543 papers · similarity ≥ 0.4 · year ≥ 2024 · Data sourced from Semantic Scholar

34,598 papers | Abstracts: 31,650 (91.5%) | Citations: 34,598 (100.0%) | arXiv: 26,074 (75.4%)

Built: Feb 15, 2026, 3:09 AM AMS

17

papers

96

total citations

papers (17)

On Optimal Robustness to Adversarial Corruption in Online Decision Problems

NEURIPS 2021arXiv

Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs

NEURIPS 2022arXiv

Single Loop Gaussian Homotopy Method for Non-convex Optimization

NEURIPS 2022arXiv

Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds

NEURIPS 2023arXiv

Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring

Adapting to Stochastic and Adversarial Losses in Episodic MDPs with Aggregate Bandit Feedback

NEURIPS 2025arXiv

Revisiting Follow-the-Perturbed-Leader with Unbounded Perturbations in Bandit Problems

NEURIPS 2025arXiv

Bandit Task Assignment with Unknown Processing Time

An Exploration-by-Optimization Approach to Best of Both Worlds in Linear Bandits

Tight First- and Second-Order Regret Bounds for Adversarial Linear Bandits

Optimal Regret of Bandits under Differential Privacy

Delay and Cooperation in Nonstochastic Linear Bandits

A Tight Lower Bound and Efficient Reduction for Swap Regret

Average Sensitivity of Euclidean k-Clustering

Optimal Dynamic Regret by Transformers for Non-Stationary Reinforcement Learning

NEURIPS 2025arXiv

New Classes of the Greedy-Applicable Arm Feature Distributions in the Sparse Linear Bandit Problem

Hybrid Regret Bounds for Combinatorial Semi-Bandits and Adversarial Linear Bandits