Taihei Oki | DeepAI

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Featured Co-authors

Shinsaku Sakaue
18 publications
Yutaro Yamaguchi
16 publications
Tasuku Soma
12 publications
Kaito Fujii
9 publications
Satoru Iwata
4 publications
Hiromichi Nagao
4 publications
Shinichi Hemmi
1 publication
Yuya Masumura
1 publication
Takashi Kurokawa
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. ∙

∙ 07/16/2022

Algebraic Algorithms for Fractional Linear Matroid Parity via Non-commutative Rank

Matrix representations are a powerful tool for designing efficient algor...

0 Taihei Oki, 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. ∙

∙ 04/23/2020

Dynamic Programming Approach to the Generalized Minimum Manhattan Network Problem

We study the generalized minimum Manhattan network (GMMN) problem: given...

0 Yuya Masumura, et al. ∙

∙ 12/02/2019

A Generalized Matrix-Tree Theorem for Pfaffian Pairs

The matrix-tree theorem counts the number of spanning trees of undirecte...

0 Taihei Oki, et al. ∙

∙ 07/10/2019

Computing the Maximum Degree of Minors in Skew Polynomial Matrices

Skew polynomials, which have a noncommutative multiplication rule betwee...

0 Taihei Oki, et al. ∙

∙ 07/10/2019

Improved Structural Methods for Nonlinear Differential-Algebraic Equations via Combinatorial Relaxation

Differential-algebraic equations (DAEs) are widely used for modeling of ...

0 Taihei Oki, et al. ∙

∙ 12/21/2017

Multi-dimensional Graph Fourier Transform

Many signals on Cartesian product graphs appear in the real world, such ...

0 Takashi Kurokawa, et al. ∙

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