Shinji Ito - RankMe

99 papers A* 37A 6B 3C 1Journal 47Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Perturbation Approach to Unconstrained Linear Bandits. CoRR Andrew Jacobsen, Dorian Baudry, Shinji Ito, Nicolò Cesa-Bianchi
2026	J	`jnl`	Adversarial Learning in Games with Bandit Feedback: Logarithmic Pure-Strategy Maximin Regret. CoRR Shinji Ito, Haipeng Luo, Arnab Maiti, Taira Tsuchiya, Yue Wu
2026	J	`jnl`	Combinatorial Allocation Bandits with Nonlinear Arm Utility. CoRR Yuki Shibukawa, Koichi Tanaka, Yuta Saito, Shinji Ito
2026	J	`jnl`	Scale-Invariant Fast Convergence in Games. CoRR Taira Tsuchiya, Haipeng Luo, Shinji Ito
2025	J	`jnl`	A Tight Lower Bound for Non-stochastic Multi-armed Bandits with Expert Advice. CoRR Zachary Chase, Shinji Ito, Idan Mehalel
2025	J	`jnl`	Adapting to Stochastic and Adversarial Losses in Episodic MDPs with Aggregate Bandit Feedback. CoRR Shinji Ito, Kevin Jamieson, Haipeng Luo, Arnab Maiti, Taira Tsuchiya
2025	—	`conf`	Bandit Max-Min Fair Allocation. ECML/PKDD (4) Tsubasa Harada, Shinji Ito, Hanna Sumita
2025	J	`jnl`	Bandit Max-Min Fair Allocation. CoRR Tsubasa Harada, Shinji Ito, Hanna Sumita
2025	A*	`conf`	Corrupted Learning Dynamics in Games. COLT Taira Tsuchiya, Shinji Ito, Haipeng Luo
2025	J	`jnl`	Data-dependent Bounds with CoRR Quan Nguyen, Shinji Ito, Junpei Komiyama, Nishant A. Mehta
2025	A*	`conf`	Data-dependent Bounds with T-Optimal Best-of-Both-Worlds Guarantees in Multi-Armed Bandits using Stability-Penalty Matching. COLT Quan M. Nguyen, Shinji Ito, Junpei Komiyama, Nishant A. Mehta
2025	J	`jnl`	Fast EXP3 Algorithms. CoRR Ryoma Sato, Shinji Ito
2025	J	`jnl`	Heavy-tailed Linear Bandits: Adversarial Robustness, Best-of-both-worlds, and Beyond. CoRR Canzhe Zhao, Shinji Ito, Shuai Li
2025	J	`jnl`	Influential Bandits: Pulling an Arm May Change the Environment. CoRR Ryoma Sato, Shinji Ito
2025	J	`jnl`	Influential Bandits: Pulling an Arm May Change the Environment. Trans. Mach. Learn. Res. Ryoma Sato, Shinji Ito
2025	A*	`conf`	Instance-Dependent Regret Bounds for Learning Two-Player Zero-Sum Games with Bandit Feedback. COLT Shinji Ito, Haipeng Luo, Taira Tsuchiya, Yue Wu
2025	J	`jnl`	Instance-Dependent Regret Bounds for Learning Two-Player Zero-Sum Games with Bandit Feedback. CoRR Shinji Ito, Haipeng Luo, Taira Tsuchiya, Yue Wu
2025	A	`conf`	LC-Tsallis-INF: Generalized Best-of-Both-Worlds Linear Contextual Bandits. AISTATS Masahiro Kato, Shinji Ito
2025	J	`jnl`	Optimal Dynamic Regret by Transformers for Non-Stationary Reinforcement Learning. CoRR Baiyuan Chen, Shinji Ito, Masaaki Imaizumi
2025	J	`jnl`	Optimal Regret of Bernoulli Bandits under Global Differential Privacy. CoRR Achraf Azize, Yulian Wu, Junya Honda, Francesco Orabona, Shinji Ito, Debabrota Basu
2025	J	`jnl`	Reinforcement Learning from Adversarial Preferences in Tabular MDPs. CoRR Taira Tsuchiya, Shinji Ito, Haipeng Luo
2025	J	`jnl`	Revisiting Follow-the-Perturbed-Leader with Unbounded Perturbations in Bandit Problems. CoRR Jongyeong Lee, Junya Honda, Shinji Ito, Min-hwan Oh
2024	A*	`conf`	A Simple and Adaptive Learning Rate for FTRL in Online Learning with Minimax Regret of $\Theta(T^{2/3})$ and its Application to Best-of-Both-Worlds. NeurIPS Taira Tsuchiya, Shinji Ito
2024	J	`jnl`	A Simple and Adaptive Learning Rate for FTRL in Online Learning with Minimax Regret of θ(T CoRR Taira Tsuchiya, Shinji Ito
2024	J	`jnl`	Active model selection: A variance minimization approach. Mach. Learn. Satoshi Hara, Mitsuru Matsuura, Junya Honda, Shinji Ito
2024	A*	`conf`	Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds. COLT Shinji Ito, Taira Tsuchiya, Junya Honda
2024	J	`jnl`	Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds. CoRR Shinji Ito, Taira Tsuchiya, Junya Honda
2024	J	`jnl`	Best-of-Both-Worlds Linear Contextual Bandits. Trans. Mach. Learn. Res. Masahiro Kato, Shinji Ito
2024	J	`jnl`	Contaminated Online Convex Optimization. Trans. Mach. Learn. Res. Tomoya Kamijima, Shinji Ito
2024	J	`jnl`	Corrupted Learning Dynamics in Games. CoRR Taira Tsuchiya, Shinji Ito, Haipeng Luo
2024	A*	`conf`	Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring. ICML Taira Tsuchiya, Shinji Ito, Junya Honda
2024	J	`jnl`	Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring. CoRR Taira Tsuchiya, Shinji Ito, Junya Honda
2024	J	`jnl`	Fast Rates in Online Convex Optimization by Exploiting the Curvature of Feasible Sets. CoRR Taira Tsuchiya, Shinji Ito
2024	A*	`conf`	Fast Rates in Stochastic Online Convex Optimization by Exploiting the Curvature of Feasible Sets. NeurIPS Taira Tsuchiya, Shinji Ito
2024	A*	`conf`	Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds. COLT Jongyeong Lee, Junya Honda, Shinji Ito, Min-hwan Oh
2024	J	`jnl`	Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds. CoRR Jongyeong Lee, Junya Honda, Shinji Ito, Min-hwan Oh
2024	J	`jnl`	LC-Tsalis-INF: Generalized Best-of-Both-Worlds Linear Contextual Bandits. CoRR Masahiro Kato, Shinji Ito
2024	A*	`conf`	Learning with Posterior Sampling for Revenue Management under Time-varying Demand. IJCAI Kazuma Shimizu, Junya Honda, Shinji Ito, Shinji Nakadai
2024	J	`jnl`	Learning with Posterior Sampling for Revenue Management under Time-varying Demand. CoRR Kazuma Shimizu, Junya Honda, Shinji Ito, Shinji Nakadai
2024	A*	`conf`	New Classes of the Greedy-Applicable Arm Feature Distributions in the Sparse Linear Bandit Problem. AAAI Koji Ichikawa, Shinji Ito, Daisuke Hatano, Hanna Sumita, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
2024	A*	`conf`	On the Minimax Regret for Contextual Linear Bandits and Multi-Armed Bandits with Expert Advice. NeurIPS Shinji Ito
2024	—	`conf`	Online $\textrm{L}^{\natural }$-Convex Minimization. ECML/PKDD (5) Ken Yokoyama, Shinji Ito, Tatsuya Matsuoka, Kei Kimura, Makoto Yokoo
2024	J	`jnl`	Online L CoRR Ken Yokoyama, Shinji Ito, Tatsuya Matsuoka, Kei Kimura, Makoto Yokoo
2024	J	`jnl`	Replicability is Asymptotically Free in Multi-armed Bandits. CoRR Junpei Komiyama, Shinji Ito, Yuichi Yoshida, Souta Koshino
2023	A*	`conf`	An Exploration-by-Optimization Approach to Best of Both Worlds in Linear Bandits. NeurIPS Shinji Ito, Kei Takemura
2023	A*	`conf`	Bandit Task Assignment with Unknown Processing Time. NeurIPS Shinji Ito, Daisuke Hatano, Hanna Sumita, Kei Takemura, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
2023	B	`conf`	Best-of-Both-Worlds Algorithms for Partial Monitoring. ALT Taira Tsuchiya, Shinji Ito, Junya Honda
2023	J	`jnl`	Best-of-Both-Worlds Linear Contextual Bandits. CoRR Masahiro Kato, Shinji Ito
2023	A*	`conf`	Best-of-Three-Worlds Linear Bandit Algorithm with Variance-Adaptive Regret Bounds. COLT Shinji Ito, Kei Takemura
2023	J	`jnl`	Best-of-Three-Worlds Linear Bandit Algorithm with Variance-Adaptive Regret Bounds. CoRR Shinji Ito, Kei Takemura
2023	B	`conf`	Follow-the-Perturbed-Leader Achieves Best-of-Both-Worlds for Bandit Problems. ALT Junya Honda, Shinji Ito, Taira Tsuchiya
2023	A	`conf`	Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits. AISTATS Taira Tsuchiya, Shinji Ito, Junya Honda
2023	C	`conf`	Maximization of Minimum Weighted Hamming Distance between Set Pairs. ACML Tatsuya Matsuoka, Shinji Ito
2023	J	`jnl`	New classes of the greedy-applicable arm feature distributions in the sparse linear bandit problem. CoRR Koji Ichikawa, Shinji Ito, Daisuke Hatano, Hanna Sumita, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
2023	J	`jnl`	Stability-penalty-adaptive Follow-the-regularized-leader: Sparsity, Game-dependency, and Best-of-both-worlds. CoRR Taira Tsuchiya, Shinji Ito, Junya Honda
2023	A*	`conf`	Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds. NeurIPS Taira Tsuchiya, Shinji Ito, Junya Honda
2022	A*	`conf`	Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds. COLT Shinji Ito, Taira Tsuchiya, Junya Honda
2022	J	`jnl`	Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds. CoRR Shinji Ito, Taira Tsuchiya, Junya Honda
2022	A*	`conf`	Average Sensitivity of Euclidean k-Clustering. NeurIPS Yuichi Yoshida, Shinji Ito
2022	J	`jnl`	Best-of-Both-Worlds Algorithms for Partial Monitoring. CoRR Taira Tsuchiya, Shinji Ito, Junya Honda
2022	A*	`conf`	Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs. NeurIPS Shinji Ito, Taira Tsuchiya, Junya Honda
2022	J	`jnl`	Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs. CoRR Shinji Ito, Taira Tsuchiya, Junya Honda
2022	A*	`conf`	Online Task Assignment Problems with Reusable Resources. AAAI Hanna Sumita, Shinji Ito, Kei Takemura, Daisuke Hatano, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
2022	J	`jnl`	Online Task Assignment Problems with Reusable Resources. CoRR Hanna Sumita, Shinji Ito, Kei Takemura, Daisuke Hatano, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
2022	A*	`conf`	Revisiting Online Submodular Minimization: Gap-Dependent Regret Bounds, Best of Both Worlds and Adversarial Robustness. ICML Shinji Ito
2022	A*	`conf`	Single Loop Gaussian Homotopy Method for Non-convex Optimization. NeurIPS Hidenori Iwakiri, Yuhang Wang, Shinji Ito, Akiko Takeda
2021	A	`conf`	A Parameter-Free Algorithm for Misspecified Linear Contextual Bandits. AISTATS Kei Takemura, Shinji Ito, Daisuke Hatano, Hanna Sumita, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
2021	A*	`conf`	Hybrid Regret Bounds for Combinatorial Semi-Bandits and Adversarial Linear Bandits. NeurIPS Shinji Ito
2021	A*	`conf`	Near-Optimal Regret Bounds for Contextual Combinatorial Semi-Bandits with Linear Payoff Functions. AAAI Kei Takemura, Shinji Ito, Daisuke Hatano, Hanna Sumita, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
2021	J	`jnl`	Near-Optimal Regret Bounds for Contextual Combinatorial Semi-Bandits with Linear Payoff Functions. CoRR Kei Takemura, Shinji Ito, Daisuke Hatano, Hanna Sumita, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
2021	A*	`conf`	On Optimal Robustness to Adversarial Corruption in Online Decision Problems. NeurIPS Shinji Ito
2021	J	`jnl`	On Optimal Robustness to Adversarial Corruption in Online Decision Problems. CoRR Shinji Ito
2021	A*	`conf`	Parameter-Free Multi-Armed Bandit Algorithms with Hybrid Data-Dependent Regret Bounds. COLT Shinji Ito
2021	A	`conf`	Tracking Regret Bounds for Online Submodular Optimization. AISTATS Tatsuya Matsuoka, Shinji Ito, Naoto Ohsaka
2020	A*	`conf`	A Tight Lower Bound and Efficient Reduction for Swap Regret. NeurIPS Shinji Ito
2020	A	`conf`	An Optimal Algorithm for Bandit Convex Optimization with Strongly-Convex and Smooth Loss. AISTATS Shinji Ito
2020	A*	`conf`	Delay and Cooperation in Nonstochastic Linear Bandits. NeurIPS Shinji Ito, Daisuke Hatano, Hanna Sumita, Kei Takemura, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
2020	A*	`conf`	Tight First- and Second-Order Regret Bounds for Adversarial Linear Bandits. NeurIPS Shinji Ito, Shuichi Hirahara, Tasuku Soma, Yuichi Yoshida
2019	A*	`conf`	An Arm-Wise Randomization Approach to Combinatorial Linear Semi-Bandits. ICDM Kei Takemura, Shinji Ito
2019	J	`jnl`	An Arm-Wise Randomization Approach to Combinatorial Linear Semi-Bandits. CoRR Kei Takemura, Shinji Ito
2019	A*	`conf`	Improved Regret Bounds for Bandit Combinatorial Optimization. NeurIPS Shinji Ito, Daisuke Hatano, Hanna Sumita, Kei Takemura, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
2019	A*	`conf`	Oracle-Efficient Algorithms for Online Linear Optimization with Bandit Feedback. NeurIPS Shinji Ito, Daisuke Hatano, Hanna Sumita, Kei Takemura, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
2019	A*	`conf`	Submodular Function Minimization with Noisy Evaluation Oracle. NeurIPS Shinji Ito
2018	A*	`conf`	Causal Bandits with Propagating Inference. ICML Akihiro Yabe, Daisuke Hatano, Hanna Sumita, Shinji Ito, Naonori Kakimura, Takuro Fukunaga, Ken-ichi Kawarabayashi
2018	J	`jnl`	Causal Bandits with Propagating Inference. CoRR Akihiro Yabe, Daisuke Hatano, Hanna Sumita, Shinji Ito, Naonori Kakimura, Takuro Fukunaga, Ken-ichi Kawarabayashi
2018	J	`jnl`	Compressed Vector Set: A Fast and Space-Efficient Data Mining Framework. J. Inf. Process. Masafumi Oyamada, Jianquan Liu, Shinji Ito, Kazuyo Narita, Takuya Araki, Hiroyuki Kitagawa
2018	A	`conf`	Online Regression with Partial Information: Generalization and Linear Projection. AISTATS Shinji Ito, Daisuke Hatano, Hanna Sumita, Akihiro Yabe, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
2018	A*	`conf`	Regret Bounds for Online Portfolio Selection with a Cardinality Constraint. NeurIPS Shinji Ito, Daisuke Hatano, Hanna Sumita, Akihiro Yabe, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
2018	J	`jnl`	Stable polefinding and rational least-squares fitting via eigenvalues. Numerische Mathematik Shinji Ito, Yuji Nakatsukasa
2018	A*	`conf`	Unbiased Objective Estimation in Predictive Optimization. ICML Shinji Ito, Akihiro Yabe, Ryohei Fujimaki
2017	—	`conf`	Efficient Sublinear-Regret Algorithms for Online Sparse Linear Regression with Limited Observation. NIPS Shinji Ito, Daisuke Hatano, Hanna Sumita, Akihiro Yabe, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
2017	A*	`conf`	Optimization Beyond Prediction: Prescriptive Price Optimization. KDD Shinji Ito, Ryohei Fujimaki
2017	A*	`conf`	Robust Quadratic Programming for Price Optimization. IJCAI Akihiro Yabe, Shinji Ito, Ryohei Fujimaki
2016	J	`jnl`	An Algorithm for the Generalized Eigenvalue Problem for Nonsquare Matrix Pencils by Minimal Perturbation Approach. SIAM J. Matrix Anal. Appl. Shinji Ito, Kazuo Murota
2016	—	`conf`	Large-Scale Price Optimization via Network Flow. NIPS Shinji Ito, Ryohei Fujimaki
2016	J	`jnl`	Optimization Beyond Prediction: Prescriptive Price Optimization. CoRR Shinji Ito, Ryohei Fujimaki
2016	B	`conf`	Supporting System for Descriptive Quiz in Large Class - Effectiveness of the Three-step-view System -. KES Shinji Ito, Tomoya Oba, Haruhiko Takase, Hiroharu Kawanaka, Shinji Tsuruoka
2015	J	`jnl`	Orthogonal polynomial approach to estimation of poles of rational functions from data on open curves. J. Comput. Appl. Math. Shinji Ito, Kensuke Aishima, Takaaki Nara, Masaaki Sugihara
2002	—	`conf`	A Parallel and Accelerated Circuit Simulator with Precise Accuracy. ASP-DAC/VLSI Design Peter M. Lee, Shinji Ito, Takeaki Hashimoto, Junji Sato, Tomomasa Touma, Goichi Yokomizo