| 2025 | AISTATS | Inverse Optimization with Prediction Market: A Characterization of Scoring Rules for Elciting System States. | Han Bao, Shinsaku Sakaue |
| 2025 | AISTATS | Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel-Young Loss Perspective and Gap-Dependent Regret Analysis. | Shinsaku Sakaue, Han Bao, Taira Tsuchiya |
| 2025 | ICML | Learning to Generate Projections for Reducing Dimensionality of Heterogeneous Linear Programming Problems. | Tomoharu Iwata, Shinsaku Sakaue |
| 2024 | COLT | 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 |
| 2023 | AISTATS | Improved Generalization Bound and Learning of Sparsity Patterns for Data-Driven Low-Rank Approximation. | Shinsaku Sakaue, Taihei Oki |
| 2023 | ICALP | Nearly Tight Spectral Sparsification of Directed Hypergraphs. | Kazusato Oko, Shinsaku Sakaue, Shin-ichi Tanigawa |
| 2023 | ICML | Rethinking Warm-Starts with Predictions: Learning Predictions Close to Sets of Optimal Solutions for Faster L-/L | Shinsaku Sakaue, Taihei Oki |
| 2022 | AAAI | Algorithmic Bayesian Persuasion with Combinatorial Actions. | Kaito Fujii, Shinsaku Sakaue |
| 2022 | GLOBECOM | Exact and Scalable Network Reliability Evaluation for Probabilistic Correlated Failures. | Ryoma Onaka, Kengo Nakamura, Takeru Inoue, Masaaki Nishino, Norihito Yasuda, Shinsaku Sakaue |
| 2021 | AISTATS | Learning Individually Fair Classifier with Path-Specific Causal-Effect Constraint. | Yoichi Chikahara, Shinsaku Sakaue, Akinori Fujino, Hisashi Kashima |
| 2021 | AISTATS | Differentiable Greedy Algorithm for Monotone Submodular Maximization: Guarantees, Gradient Estimators, and Applications. | Shinsaku Sakaue |
| 2020 | AAAI | Practical Frank-Wolfe Method with Decision Diagrams for Computing Wardrop Equilibrium of Combinatorial Congestion Games. | Kengo Nakamura, Shinsaku Sakaue, Norihito Yasuda |
| 2020 | AISTATS | Guarantees of Stochastic Greedy Algorithms for Non-monotone Submodular Maximization with Cardinality Constraint. | Shinsaku Sakaue |
| 2020 | AISTATS | On Maximization of Weakly Modular Functions: Guarantees of Multi-stage Algorithms, Tractability, and Hardness. | Shinsaku Sakaue |
| 2019 | AISTATS | Greedy and IHT Algorithms for Non-convex Optimization with Monotone Costs of Non-zeros. | Shinsaku Sakaue |
| 2019 | ICML | Beyond Adaptive Submodularity: Approximation Guarantees of Greedy Policy with Adaptive Submodularity Ratio. | Kaito Fujii, Shinsaku Sakaue |
| 2018 | AAAI | Accelerated Best-First Search With Upper-Bound Computation for Submodular Function Maximization. | Shinsaku Sakaue, Masakazu Ishihata |
| 2018 | AAAI | Submodular Function Maximization Over Graphs via Zero-Suppressed Binary Decision Diagrams. | Shinsaku Sakaue, Masaaki Nishino, Norihito Yasuda |
| 2018 | AISTATS | Efficient Bandit Combinatorial Optimization Algorithm with Zero-suppressed Binary Decision Diagrams. | Shinsaku Sakaue, Masakazu Ishihata, Shin-ichi Minato |
| 2018 | NAACL | Provable Fast Greedy Compressive Summarization with Any Monotone Submodular Function. | Shinsaku Sakaue, Tsutomu Hirao, Masaaki Nishino, Masaaki Nagata |