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ORCIDShinsaku Sakaue
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2020 – today
- 2024
[c22]Shinsaku Sakaue, Han Bao, Taira Tsuchiya, Taihei Oki:
Online Structured Prediction with Fenchel-Young Losses and Improved Surrogate Regret for Online Multiclass Classification with Logistic Loss. COLT 2024: 4458-4486- [i21]Shinsaku Sakaue, Han Bao, Taira Tsuchiya, Taihei Oki:
Online Structured Prediction with Fenchel-Young Losses and Improved Surrogate Regret for Online Multiclass Classification with Logistic Loss. CoRR abs/2402.08180 (2024) - [i20]Taihei Oki, Shinsaku Sakaue:
No-Regret M♮-Concave Function Maximization: Stochastic Bandit Algorithms and NP-Hardness of Adversarial Full-Information Setting. CoRR abs/2405.12439 (2024) - 2023
- [j5]Yoichi Chikahara
, Shinsaku Sakaue, Akinori Fujino, Hisashi Kashima:
Making individually fair predictions with causal pathways. Data Min. Knowl. Discov. 37(4): 1327-1373 (2023) - [c21]Shinsaku Sakaue, Taihei Oki:
Improved Generalization Bound and Learning of Sparsity Patterns for Data-Driven Low-Rank Approximation. AISTATS 2023: 1-10 - [c20]Kazusato Oko, Shinsaku Sakaue, Shin-ichi Tanigawa:
Nearly Tight Spectral Sparsification of Directed Hypergraphs. ICALP 2023: 94:1-94:19 - [c19]Shinsaku Sakaue, Taihei Oki:
Rethinking Warm-Starts with Predictions: Learning Predictions Close to Sets of Optimal Solutions for Faster L-/L♮-Convex Function Minimization. ICML 2023: 29760-29776 - [c18]Taihei Oki, Shinsaku Sakaue:
Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case. NeurIPS 2023 - [i19]Shinsaku Sakaue, Taihei Oki:
Rethinking Warm-Starts with Predictions: Learning Predictions Close to Sets of Optimal Solutions for Faster L-/L♮-Convex Function Minimization. CoRR abs/2302.00928 (2023) - [i18]Taihei Oki, Shinsaku Sakaue:
Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case. CoRR abs/2306.05865 (2023) - [i17]Shinsaku Sakaue, Taihei Oki:
Data-Driven Projection for Reducing Dimensionality of Linear Programs: Generalization Bound and Learning Methods. CoRR abs/2309.00203 (2023) - [i16]Satoru Iwata, Taihei Oki, Shinsaku Sakaue:
Rate Constant Matrix Contraction Method for Stiff Master Equations with Detailed Balance. CoRR abs/2312.05470 (2023) - 2022
- [j4]Han Bao, Shinsaku Sakaue:
Sparse Regularized Optimal Transport with Deformed q-Entropy. Entropy 24(11): 1634 (2022) - [c17]Kaito Fujii, Shinsaku Sakaue:
Algorithmic Bayesian Persuasion with Combinatorial Actions. AAAI 2022: 5016-5024 - [c16]Ryoma Onaka, Kengo Nakamura, Takeru Inoue, Masaaki Nishino, Norihito Yasuda, Shinsaku Sakaue:
Exact and Scalable Network Reliability Evaluation for Probabilistic Correlated Failures. GLOBECOM 2022: 5547-5552 - [c15]Shinichi Hemmi, Taihei Oki, Shinsaku Sakaue, Kaito Fujii, Satoru Iwata:
Lazy and Fast Greedy MAP Inference for Determinantal Point Process. NeurIPS 2022 - [c14]Shinsaku Sakaue, Taihei Oki:
Sample Complexity of Learning Heuristic Functions for Greedy-Best-First and A* Search. NeurIPS 2022 - [c13]Shinsaku Sakaue, Taihei Oki:
Discrete-Convex-Analysis-Based Framework for Warm-Starting Algorithms with Predictions. NeurIPS 2022 - [i15]Kazusato Oko, Shinsaku Sakaue, Shin-ichi Tanigawa:
Nearly Tight Spectral Sparsification of Directed Hypergraphs by a Simple Iterative Sampling Algorithm. CoRR abs/2204.02537 (2022) - [i14]Shinsaku Sakaue, Taihei Oki:
Discrete-Convex-Analysis-Based Framework for Warm-Starting Algorithms with Predictions. CoRR abs/2205.09961 (2022) - [i13]Shinsaku Sakaue, Taihei Oki:
Sample Complexity of Learning Heuristic Functions for Greedy-Best-First and A* Search. CoRR abs/2205.09963 (2022) - [i12]Shinichi Hemmi, Taihei Oki, Shinsaku Sakaue, Kaito Fujii, Satoru Iwata:
Lazy and Fast Greedy MAP Inference for Determinantal Point Process. CoRR abs/2206.05947 (2022) - [i11]Shinsaku Sakaue, Taihei Oki:
Improved Generalization Bound and Learning of Sparsity Patterns for Data-Driven Low-Rank Approximation. CoRR abs/2209.08281 (2022) - 2021
- [c12]Shinsaku Sakaue:
Differentiable Greedy Algorithm for Monotone Submodular Maximization: Guarantees, Gradient Estimators, and Applications. AISTATS 2021: 28-36 - [c11]Yoichi Chikahara, Shinsaku Sakaue, Akinori Fujino, Hisashi Kashima:
Learning Individually Fair Classifier with Path-Specific Causal-Effect Constraint. AISTATS 2021: 145-153 - [c10]Shinsaku Sakaue, Kengo Nakamura:
Differentiable Equilibrium Computation with Decision Diagrams for Stackelberg Models of Combinatorial Congestion Games. NeurIPS 2021: 9416-9428 - [i10]Shinsaku Sakaue, Kengo Nakamura:
Differentiable Equilibrium Computation with Decision Diagrams for Stackelberg Models of Combinatorial Congestion Games. CoRR abs/2110.01773 (2021) - [i9]Kaito Fujii, Shinsaku Sakaue:
Algorithmic Bayesian persuasion with combinatorial actions. CoRR abs/2112.06282 (2021) - 2020
- [b1]Shinsaku Sakaue:
Online, Submodular, and Polynomial Optimization with Discrete Structures. Kyoto University, Japan, 2020 - [c9]Kengo Nakamura, Shinsaku Sakaue, Norihito Yasuda:
Practical Frank-Wolfe Method with Decision Diagrams for Computing Wardrop Equilibrium of Combinatorial Congestion Games. AAAI 2020: 2200-2209 - [c8]Shinsaku Sakaue:
Guarantees of Stochastic Greedy Algorithms for Non-monotone Submodular Maximization with Cardinality Constraint. AISTATS 2020: 11-21 - [c7]Shinsaku Sakaue:
On Maximization of Weakly Modular Functions: Guarantees of Multi-stage Algorithms, Tractability, and Hardness. AISTATS 2020: 22-33 - [i8]Yoichi Chikahara, Shinsaku Sakaue, Akinori Fujino:
Learning Individually Fair Classifier with Causal-Effect Constraint. CoRR abs/2002.06746 (2020) - [i7]Shinsaku Sakaue:
Differentiable Greedy Submodular Maximization: Guarantees, Gradient Estimators, and Applications. CoRR abs/2005.02578 (2020)
2010 – 2019
- 2019
- [c6]Shinsaku Sakaue:
Greedy and IHT Algorithms for Non-convex Optimization with Monotone Costs of Non-zeros. AISTATS 2019: 206-215 - [c5]Kaito Fujii, Shinsaku Sakaue:
Beyond Adaptive Submodularity: Approximation Guarantees of Greedy Policy with Adaptive Submodularity Ratio. ICML 2019: 2042-2051 - [i6]Kaito Fujii, Shinsaku Sakaue:
Beyond Adaptive Submodularity: Approximation Guarantees of Greedy Policy with Adaptive Submodularity Ratio. CoRR abs/1904.10748 (2019) - [i5]Shinsaku Sakaue:
Approximation Guarantees of Stochastic Greedy Algorithms for Non-monotone Submodular Maximization with a Size Constraint. CoRR abs/1908.06242 (2019) - [i4]Shinsaku Sakaue, Naoki Marumo:
Best-first Search Algorithm for Non-convex Sparse Minimization. CoRR abs/1910.01296 (2019) - 2018
- [c4]Shinsaku Sakaue, Masakazu Ishihata:
Accelerated Best-First Search With Upper-Bound Computation for Submodular Function Maximization. AAAI 2018: 1413-1421 - [c3]Shinsaku Sakaue, Masaaki Nishino, Norihito Yasuda:
Submodular Function Maximization Over Graphs via Zero-Suppressed Binary Decision Diagrams. AAAI 2018: 1422-1430 - [c2]Shinsaku Sakaue, Masakazu Ishihata, Shin-ichi Minato:
Efficient Bandit Combinatorial Optimization Algorithm with Zero-suppressed Binary Decision Diagrams. AISTATS 2018: 585-594 - [c1]Shinsaku Sakaue, Tsutomu Hirao, Masaaki Nishino, Masaaki Nagata:
Provable Fast Greedy Compressive Summarization with Any Monotone Submodular Function. NAACL-HLT 2018: 1737-1746 - [i3]Shinsaku Sakaue:
Weak Supermodularity Assists Submodularity-based Approaches to Non-convex Constrained Optimization. CoRR abs/1805.11251 (2018) - 2017
- [j3]Shinsaku Sakaue:
On maximizing a monotone k-submodular function subject to a matroid constraint. Discret. Optim. 23: 105-113 (2017) - [j2]Shinsaku Sakaue, Akiko Takeda, Sunyoung Kim, Naoki Ito:
Exact Semidefinite Programming Relaxations with Truncated Moment Matrix for Binary Polynomial Optimization Problems. SIAM J. Optim. 27(1): 565-582 (2017) - [i2]Shinsaku Sakaue, Masakazu Ishihata, Shin-ichi Minato:
Practical Adversarial Combinatorial Bandit Algorithm via Compression of Decision Sets. CoRR abs/1707.08300 (2017) - 2016
- [j1]Shinsaku Sakaue, Yuji Nakatsukasa, Akiko Takeda, Satoru Iwata:
Solving Generalized CDT Problems via Two-Parameter Eigenvalues. SIAM J. Optim. 26(3): 1669-1694 (2016) - [i1]Shinsaku Sakaue:
On maximizing a monotone k-submodular function subject to a matroid constraint. CoRR abs/1607.07957 (2016)
Coauthor Index
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