Shinsaku Sakaue | DeepAI

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Featured Co-authors

Taihei Oki
13 publications
Kaito Fujii
9 publications
Akinori Fujino
5 publications
Satoru Iwata
4 publications
Kazusato Oko
4 publications
Naoki Marumo
4 publications
Shin-ichi Tanigawa
3 publications
Kengo Nakamura
3 publications
Yoichi Chikahara
3 publications
Shinichi Hemmi
1 publication

∙ 09/01/2023

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

This paper studies a simple data-driven approach to high-dimensional lin...

0 Shinsaku Sakaue, et al. ∙

∙ 06/09/2023

Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case

Recent years have seen a growing interest in accelerating optimization a...

0 Taihei Oki, et al. ∙

∙ 02/02/2023

Rethinking Warm-Starts with Predictions: Learning Predictions Close to Sets of Optimal Solutions for Faster L-/L^♮-Convex Function Minimization

An emerging line of work has shown that machine-learned predictions are ...

0 Shinsaku Sakaue, et al. ∙

∙ 09/17/2022

Improved Generalization Bound and Learning of Sparsity Patterns for Data-Driven Low-Rank Approximation

Learning sketching matrices for fast and accurate low-rank approximation...

0 Shinsaku Sakaue, et al. ∙

∙ 06/13/2022

Lazy and Fast Greedy MAP Inference for Determinantal Point Process

The maximum a posteriori (MAP) inference for determinantal point process...

0 Shinichi Hemmi, et al. ∙

∙ 05/20/2022

Sample Complexity of Learning Heuristic Functions for Greedy-Best-First and A* Search

Greedy best-first search (GBFS) and A* search (A*) are popular algorithm...

0 Shinsaku Sakaue, et al. ∙

∙ 05/20/2022

Discrete-Convex-Analysis-Based Framework for Warm-Starting Algorithms with Predictions

Augmenting algorithms with learned predictions is a promising approach f...

0 Shinsaku Sakaue, et al. ∙

∙ 04/06/2022

Nearly Tight Spectral Sparsification of Directed Hypergraphs by a Simple Iterative Sampling Algorithm

Spectral hypergraph sparsification, which is an attempt to extend well-k...

0 Kazusato Oko, et al. ∙

∙ 12/12/2021

Algorithmic Bayesian persuasion with combinatorial actions

Bayesian persuasion is a model for understanding strategic information r...

0 Kaito Fujii, et al. ∙

∙ 10/05/2021

Differentiable Equilibrium Computation with Decision Diagrams for Stackelberg Models of Combinatorial Congestion Games

We address Stackelberg models of combinatorial congestion games (CCGs); ...

0 Shinsaku Sakaue, et al. ∙

∙ 05/06/2020

Differentiable Greedy Submodular Maximization: Guarantees, Gradient Estimators, and Applications

We consider making outputs of the greedy algorithm for monotone submodul...

0 Shinsaku Sakaue, et al. ∙

∙ 05/06/2020

Differentiable Greedy Submodular Maximization with Guarantees and Gradient Estimators

We consider making outputs of the greedy algorithm for monotone submodul...

0 Shinsaku Sakaue, et al. ∙

∙ 02/17/2020

Learning Individually Fair Classifier with Causal-Effect Constraint

Machine learning is increasingly being used in various applications that...

0 Yoichi Chikahara, et al. ∙

∙ 10/03/2019

Best-first Search Algorithm for Non-convex Sparse Minimization

Non-convex sparse minimization (NSM), or ℓ_0-constrained minimization of...

0 Shinsaku Sakaue, et al. ∙

∙ 08/17/2019

Guarantees of Stochastic Greedy Algorithms for Non-monotone Submodular Maximization with Cardinality Constraint

Submodular maximization with a cardinality constraint can model various ...

0 Shinsaku Sakaue, et al. ∙

∙ 08/17/2019

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

The stochastic greedy algorithm (SG) is a randomized version of the gree...

0 Shinsaku Sakaue, et al. ∙

∙ 04/24/2019

Beyond Adaptive Submodularity: Approximation Guarantees of Greedy Policy with Adaptive Submodularity Ratio

We propose a new concept named adaptive submodularity ratio to study the...

0 Kaito Fujii, et al. ∙

∙ 05/29/2018

Weak Supermodularity Assists Submodularity-based Approaches to Non-convex Constrained Optimization

Non-convex constrained optimization problems have many applications in m...

0 Shinsaku Sakaue, et al. ∙

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