Shinji Ito

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 67

Top Topics

Quadratic Program

Online Learning

Convex Optimization

Top Venues

Publications

Masahiro Kato, Shinji Ito
Best-of-Both-Worlds Linear Contextual Bandits. Trans. Mach. Learn. Res. 2024 (2024)
Taira Tsuchiya, Shinji Ito
Fast Rates in Online Convex Optimization by Exploiting the Curvature of Feasible Sets. CoRR (2024)
Ken Yokoyama, Shinji Ito, Tatsuya Matsuoka, Kei Kimura, Makoto Yokoo
-Convex Minimization. CoRR (2024)
Koji Ichikawa, Shinji Ito, Daisuke Hatano, Hanna Sumita, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
New Classes of the Greedy-Applicable Arm Feature Distributions in the Sparse Linear Bandit Problem. AAAI (2024)
Jongyeong Lee, Junya Honda, Shinji Ito, Min-hwan Oh
Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds. CoRR (2024)
Jongyeong Lee, Junya Honda, Shinji Ito, Min-hwan Oh
Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds. COLT (2024)
Masahiro Kato, Shinji Ito
LC-Tsalis-INF: Generalized Best-of-Both-Worlds Linear Contextual Bandits. CoRR (2024)
Taira Tsuchiya, Shinji Ito
) and its Application to Best-of-Both-Worlds. CoRR (2024)
Kazuma Shimizu, Junya Honda, Shinji Ito, Shinji Nakadai
Learning with Posterior Sampling for Revenue Management under Time-varying Demand. CoRR (2024)
Taira Tsuchiya, Shinji Ito, Junya Honda
Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring. CoRR (2024)
Shinji Ito, Taira Tsuchiya, Junya Honda
Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds. COLT (2024)
Shinji Ito, Taira Tsuchiya, Junya Honda
Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds. CoRR (2024)
Junpei Komiyama, Shinji Ito, Yuichi Yoshida, Souta Koshino
Replicability is Asymptotically Free in Multi-armed Bandits. CoRR (2024)
Shinji Ito, Daisuke Hatano, Hanna Sumita, Kei Takemura, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
Bandit Task Assignment with Unknown Processing Time. NeurIPS (2023)
Tatsuya Matsuoka, Shinji Ito
Maximization of Minimum Weighted Hamming Distance between Set Pairs. ACML (2023)
Koji Ichikawa, Shinji Ito, Daisuke Hatano, Hanna Sumita, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
New classes of the greedy-applicable arm feature distributions in the sparse linear bandit problem. CoRR (2023)
Shinji Ito, Kei Takemura
Best-of-Three-Worlds Linear Bandit Algorithm with Variance-Adaptive Regret Bounds. COLT (2023)
Shinji Ito, Kei Takemura
Best-of-Three-Worlds Linear Bandit Algorithm with Variance-Adaptive Regret Bounds. CoRR (2023)
Taira Tsuchiya, Shinji Ito, Junya Honda
Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds. NeurIPS (2023)
Taira Tsuchiya, Shinji Ito, Junya Honda
Best-of-Both-Worlds Algorithms for Partial Monitoring. ALT (2023)
Taira Tsuchiya, Shinji Ito, Junya Honda
Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits. AISTATS (2023)
Junya Honda, Shinji Ito, Taira Tsuchiya
Follow-the-Perturbed-Leader Achieves Best-of-Both-Worlds for Bandit Problems. ALT (2023)
Taira Tsuchiya, Shinji Ito, Junya Honda
Stability-penalty-adaptive Follow-the-regularized-leader: Sparsity, Game-dependency, and Best-of-both-worlds. CoRR (2023)
Masahiro Kato, Shinji Ito
Best-of-Both-Worlds Linear Contextual Bandits. CoRR (2023)
Shinji Ito, Kei Takemura
An Exploration-by-Optimization Approach to Best of Both Worlds in Linear Bandits. NeurIPS (2023)
Shinji Ito, Taira Tsuchiya, Junya Honda
Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs. CoRR (2022)
Shinji Ito, Taira Tsuchiya, Junya Honda
Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds. CoRR (2022)
Hanna Sumita, Shinji Ito, Kei Takemura, Daisuke Hatano, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
Online Task Assignment Problems with Reusable Resources. AAAI (2022)
Shinji Ito
Revisiting Online Submodular Minimization: Gap-Dependent Regret Bounds, Best of Both Worlds and Adversarial Robustness. ICML (2022)
Hidenori Iwakiri, Yuhang Wang, Shinji Ito, Akiko Takeda
Single Loop Gaussian Homotopy Method for Non-convex Optimization. NeurIPS (2022)
Shinji Ito, Taira Tsuchiya, Junya Honda
Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds. COLT (2022)
Yuichi Yoshida, Shinji Ito
Average Sensitivity of Euclidean k-Clustering. NeurIPS (2022)
Taira Tsuchiya, Shinji Ito, Junya Honda
Best-of-Both-Worlds Algorithms for Partial Monitoring. CoRR (2022)
Hanna Sumita, Shinji Ito, Kei Takemura, Daisuke Hatano, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
Online Task Assignment Problems with Reusable Resources. CoRR (2022)
Shinji Ito, Taira Tsuchiya, Junya Honda
Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs. NeurIPS (2022)
Shinji Ito
On Optimal Robustness to Adversarial Corruption in Online Decision Problems. CoRR (2021)
Shinji Ito
Parameter-Free Multi-Armed Bandit Algorithms with Hybrid Data-Dependent Regret Bounds. COLT (2021)
Kei Takemura, Shinji Ito, Daisuke Hatano, Hanna Sumita, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
Near-Optimal Regret Bounds for Contextual Combinatorial Semi-Bandits with Linear Payoff Functions. CoRR (2021)
Shinji Ito
Hybrid Regret Bounds for Combinatorial Semi-Bandits and Adversarial Linear Bandits. NeurIPS (2021)
Shinji Ito
On Optimal Robustness to Adversarial Corruption in Online Decision Problems. NeurIPS (2021)
Kei Takemura, Shinji Ito, Daisuke Hatano, Hanna Sumita, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
A Parameter-Free Algorithm for Misspecified Linear Contextual Bandits. AISTATS (2021)
Kei Takemura, Shinji Ito, Daisuke Hatano, Hanna Sumita, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
Near-Optimal Regret Bounds for Contextual Combinatorial Semi-Bandits with Linear Payoff Functions. AAAI (2021)
Tatsuya Matsuoka, Shinji Ito, Naoto Ohsaka
Tracking Regret Bounds for Online Submodular Optimization. AISTATS (2021)
Shinji Ito
An Optimal Algorithm for Bandit Convex Optimization with Strongly-Convex and Smooth Loss. AISTATS (2020)
Shinji Ito, Shuichi Hirahara, Tasuku Soma, Yuichi Yoshida
Tight First- and Second-Order Regret Bounds for Adversarial Linear Bandits. NeurIPS (2020)
Shinji Ito
A Tight Lower Bound and Efficient Reduction for Swap Regret. NeurIPS (2020)
Shinji Ito, Daisuke Hatano, Hanna Sumita, Kei Takemura, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
Delay and Cooperation in Nonstochastic Linear Bandits. NeurIPS (2020)
Kei Takemura, Shinji Ito
An Arm-Wise Randomization Approach to Combinatorial Linear Semi-Bandits. ICDM (2019)
Shinji Ito, Daisuke Hatano, Hanna Sumita, Kei Takemura, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
Oracle-Efficient Algorithms for Online Linear Optimization with Bandit Feedback. NeurIPS (2019)
Shinji Ito, Daisuke Hatano, Hanna Sumita, Kei Takemura, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
Improved Regret Bounds for Bandit Combinatorial Optimization. NeurIPS (2019)
Kei Takemura, Shinji Ito
An Arm-Wise Randomization Approach to Combinatorial Linear Semi-Bandits. CoRR (2019)
Shinji Ito
Submodular Function Minimization with Noisy Evaluation Oracle. NeurIPS (2019)
Akihiro Yabe, Daisuke Hatano, Hanna Sumita, Shinji Ito, Naonori Kakimura, Takuro Fukunaga, Ken-ichi Kawarabayashi
Causal Bandits with Propagating Inference. ICML (2018)
Shinji Ito, Yuji Nakatsukasa
Stable polefinding and rational least-squares fitting via eigenvalues. Numerische Mathematik 139 (3) (2018)
Shinji Ito, Daisuke Hatano, Hanna Sumita, Akihiro Yabe, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
Regret Bounds for Online Portfolio Selection with a Cardinality Constraint. NeurIPS (2018)
Masafumi Oyamada, Jianquan Liu, Shinji Ito, Kazuyo Narita, Takuya Araki, Hiroyuki Kitagawa
Compressed Vector Set: A Fast and Space-Efficient Data Mining Framework. J. Inf. Process. 26 (2018)
Shinji Ito, Daisuke Hatano, Hanna Sumita, Akihiro Yabe, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
Online Regression with Partial Information: Generalization and Linear Projection. AISTATS (2018)
Akihiro Yabe, Daisuke Hatano, Hanna Sumita, Shinji Ito, Naonori Kakimura, Takuro Fukunaga, Ken-ichi Kawarabayashi
Causal Bandits with Propagating Inference. CoRR (2018)
Shinji Ito, Akihiro Yabe, Ryohei Fujimaki
Unbiased Objective Estimation in Predictive Optimization. ICML (2018)
Shinji Ito, Daisuke Hatano, Hanna Sumita, Akihiro Yabe, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
Efficient Sublinear-Regret Algorithms for Online Sparse Linear Regression with Limited Observation. NIPS (2017)
Shinji Ito, Ryohei Fujimaki
Optimization Beyond Prediction: Prescriptive Price Optimization. KDD (2017)
Akihiro Yabe, Shinji Ito, Ryohei Fujimaki
Robust Quadratic Programming for Price Optimization. IJCAI (2017)
Shinji Ito, Ryohei Fujimaki
Large-Scale Price Optimization via Network Flow. NIPS (2016)
Shinji Ito, Tomoya Oba, Haruhiko Takase, Hiroharu Kawanaka, Shinji Tsuruoka
Supporting System for Descriptive Quiz in Large Class - Effectiveness of the Three-step-view System -. KES (2016)
Shinji Ito, Ryohei Fujimaki
Optimization Beyond Prediction: Prescriptive Price Optimization. CoRR (2016)
Shinji Ito, Kazuo Murota
An Algorithm for the Generalized Eigenvalue Problem for Nonsquare Matrix Pencils by Minimal Perturbation Approach. SIAM J. Matrix Anal. Appl. 37 (1) (2016)
Shinji Ito, Kensuke Aishima, Takaaki Nara, Masaaki Sugihara
Orthogonal polynomial approach to estimation of poles of rational functions from data on open curves. J. Comput. Appl. Math. 273 (2015)
Peter M. Lee, Shinji Ito, Takeaki Hashimoto, Junji Sato, Tomomasa Touma, Goichi Yokomizo
A Parallel and Accelerated Circuit Simulator with Precise Accuracy. VLSI Design (2002)