Shinsaku Sakaue

According to our database1, Shinsaku Sakaue authored at least 37 papers between 2016 and 2024.

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Bibliography

2024
Online Structured Prediction with Fenchel-Young Losses and Improved Surrogate Regret for Online Multiclass Classification with Logistic Loss.
CoRR, 2024

2023
Making individually fair predictions with causal pathways.
Data Min. Knowl. Discov., 2023

Rate Constant Matrix Contraction Method for Stiff Master Equations with Detailed Balance.
CoRR, 2023

Data-Driven Projection for Reducing Dimensionality of Linear Programs: Generalization Bound and Learning Methods.
CoRR, 2023

Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Rethinking Warm-Starts with Predictions: Learning Predictions Close to Sets of Optimal Solutions for Faster L-/L<sup>♮</sup>-Convex Function Minimization.
Proceedings of the International Conference on Machine Learning, 2023

Nearly Tight Spectral Sparsification of Directed Hypergraphs.
Proceedings of the 50th International Colloquium on Automata, Languages, and Programming, 2023

Improved Generalization Bound and Learning of Sparsity Patterns for Data-Driven Low-Rank Approximation.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Sparse Regularized Optimal Transport with Deformed q-Entropy.
Entropy, 2022

Nearly Tight Spectral Sparsification of Directed Hypergraphs by a Simple Iterative Sampling Algorithm.
CoRR, 2022

Discrete-Convex-Analysis-Based Framework for Warm-Starting Algorithms with Predictions.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sample Complexity of Learning Heuristic Functions for Greedy-Best-First and A* Search.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Lazy and Fast Greedy MAP Inference for Determinantal Point Process.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Exact and Scalable Network Reliability Evaluation for Probabilistic Correlated Failures.
Proceedings of the IEEE Global Communications Conference, 2022

Algorithmic Bayesian Persuasion with Combinatorial Actions.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Differentiable Equilibrium Computation with Decision Diagrams for Stackelberg Models of Combinatorial Congestion Games.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Differentiable Greedy Algorithm for Monotone Submodular Maximization: Guarantees, Gradient Estimators, and Applications.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Learning Individually Fair Classifier with Path-Specific Causal-Effect Constraint.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Online, Submodular, and Polynomial Optimization with Discrete Structures.
PhD thesis, 2020

Differentiable Greedy Submodular Maximization: Guarantees, Gradient Estimators, and Applications.
CoRR, 2020

Learning Individually Fair Classifier with Causal-Effect Constraint.
CoRR, 2020

On Maximization of Weakly Modular Functions: Guarantees of Multi-stage Algorithms, Tractability, and Hardness.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Guarantees of Stochastic Greedy Algorithms for Non-monotone Submodular Maximization with Cardinality Constraint.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Practical Frank-Wolfe Method with Decision Diagrams for Computing Wardrop Equilibrium of Combinatorial Congestion Games.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Best-first Search Algorithm for Non-convex Sparse Minimization.
CoRR, 2019

Approximation Guarantees of Stochastic Greedy Algorithms for Non-monotone Submodular Maximization with a Size Constraint.
CoRR, 2019

Beyond Adaptive Submodularity: Approximation Guarantees of Greedy Policy with Adaptive Submodularity Ratio.
Proceedings of the 36th International Conference on Machine Learning, 2019

Greedy and IHT Algorithms for Non-convex Optimization with Monotone Costs of Non-zeros.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Weak Supermodularity Assists Submodularity-based Approaches to Non-convex Constrained Optimization.
CoRR, 2018

Provable Fast Greedy Compressive Summarization with Any Monotone Submodular Function.
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

Efficient Bandit Combinatorial Optimization Algorithm with Zero-suppressed Binary Decision Diagrams.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Submodular Function Maximization Over Graphs via Zero-Suppressed Binary Decision Diagrams.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Accelerated Best-First Search With Upper-Bound Computation for Submodular Function Maximization.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Exact Semidefinite Programming Relaxations with Truncated Moment Matrix for Binary Polynomial Optimization Problems.
SIAM J. Optim., 2017

On maximizing a monotone k-submodular function subject to a matroid constraint.
Discret. Optim., 2017

Practical Adversarial Combinatorial Bandit Algorithm via Compression of Decision Sets.
CoRR, 2017

2016
Solving Generalized CDT Problems via Two-Parameter Eigenvalues.
SIAM J. Optim., 2016


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