Oki, Taihei

10 publications

NeurIPS 2025 Online Inverse Linear Optimization: Efficient Logarithmic-Regret Algorithm, Robustness to Suboptimality, and Lower Bound Shinsaku Sakaue, Taira Tsuchiya, Han Bao, Taihei Oki

NeurIPS 2024 Generalization Bound and Learning Methods for Data-Driven Projections in Linear Programming Shinsaku Sakaue, Taihei Oki

NeurIPS 2024 No-Regret M${}^{\natural}$-Concave Function Maximization: Stochastic Bandit Algorithms and NP-Hardness of Adversarial Full-Information Setting Taihei Oki, Shinsaku Sakaue

COLT 2024 Online Structured Prediction with Fenchel–Young Losses and Improved Surrogate Regret for Online Multiclass Classification with Logistic Loss Shinsaku Sakaue, Han Bao, Taira Tsuchiya, Taihei Oki

NeurIPS 2023 Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case Taihei Oki, Shinsaku Sakaue

AISTATS 2023 Improved Generalization Bound and Learning of Sparsity Patterns for Data-Driven Low-Rank Approximation Shinsaku Sakaue, Taihei Oki

ICML 2023 Rethinking Warm-Starts with Predictions: Learning Predictions Close to Sets of Optimal Solutions for Faster $\text{L}$-/$\text{L}^\natural$-Convex Function Minimization Shinsaku Sakaue, Taihei Oki

NeurIPS 2022 Discrete-Convex-Analysis-Based Framework for Warm-Starting Algorithms with Predictions Shinsaku Sakaue, Taihei Oki

NeurIPS 2022 Lazy and Fast Greedy MAP Inference for Determinantal Point Process Shinichi Hemmi, Taihei Oki, Shinsaku Sakaue, Kaito Fujii, Satoru Iwata

NeurIPS 2022 Sample Complexity of Learning Heuristic Functions for Greedy-Best-First and A* Search Shinsaku Sakaue, Taihei Oki