Masakazu Muramatsu

According to our database1, Masakazu Muramatsu authored at least 33 papers between 1995 and 2024.

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Bibliography

2024
Closing duality gaps of SDPs completely through perturbation when singularity degree is one.
Optim. Methods Softw., 2024

2023
Shift Quality Classifier Using Deep Neural Networks on Small Data with Dropout and Semi-Supervised Learning.
IEICE Trans. Inf. Syst., December, 2023

A limiting analysis on regularization of singular SDP and its implication to infeasible interior-point algorithms.
Math. Program., 2023

2022
A Variant of Knapsack Problem Efficient for Benders Decomposition.
Proceedings of the 2022 13th International Congress on Advanced Applied Informatics Winter, 2022

2021
Solving SDP completely with an interior point oracle.
Optim. Methods Softw., 2021

2020
Development of Artificial Intelligence to Classify Quality of Transmission Shift Control Using Deep Convolutional Neural Networks.
IEEE Trans. Veh. Technol., 2020

2019
An extension of Chubanov's algorithm to symmetric cones.
Math. Program., 2019

Approach to problem of minimizing network power consumption based on robust optimization.
Int. J. Commun. Syst., 2019

2018
Facial Reduction and Partial Polyhedrality.
SIAM J. Optim., 2018

Network Congestion Minimization Models Based on Robust Optimization.
IEICE Trans. Commun., 2018

2017
Improved simulation adjusting.
J. Int. Comput. Games Assoc., 2017

2016
Perturbed sums-of-squares theorem for polynomial optimization and its applications.
Optim. Methods Softw., 2016

Weak infeasibility in second order cone programming.
Optim. Lett., 2016

Pure Nash equilibria of competitive diffusion process on toroidal grid graphs.
Discret. Appl. Math., 2016

2014
Monte-Carlo Simulation Adjusting.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Facial Reduction Algorithms for Conic Optimization Problems.
J. Optim. Theory Appl., 2013

2012
Efficiency of three forward-pruning techniques in shogi: Futility pruning, null-move pruning, and Late Move Reduction (LMR).
Entertain. Comput., 2012

Strange behaviors of interior-point methods for solving semidefinite programming problems in polynomial optimization.
Comput. Optim. Appl., 2012

2010
A facial reduction algorithm for finding sparse SOS representations.
Oper. Res. Lett., 2010

2009
Implementation Issues of Second-Order Cone Programming Approaches for Support Vector Machine Learning Problems.
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2009

A note on sparse SOS and SDP relaxations for polynomial optimization problems over symmetric cones.
Comput. Optim. Appl., 2009

2008
Algorithm 883: SparsePOP - A Sparse Semidefinite Programming Relaxation of Polynomial Optimization Problems.
ACM Trans. Math. Softw., 2008

2007
An Extension of Sums of Squares Relaxations to Polynomial Optimization Problems Over Symmetric Cones.
Math. Program., 2007

2006
Sums of Squares and Semidefinite Program Relaxations for Polynomial Optimization Problems with Structured Sparsity.
SIAM J. Optim., 2006

A pivoting procedure for a class of second-order cone programming.
Optim. Methods Softw., 2006

2005
An Efficient Support Vector Machine Learning Method with Second-Order Cone Programming for Large-Scale Problems.
Appl. Intell., 2005

A Unified Class of Directly Solvable Semidefinite Programming Problems.
Ann. Oper. Res., 2005

2004
A New Model for Large Margin Classifiers by Second Order Cone Programming.
Proceedings of the International Conference on Artificial Intelligence, 2004

1999
Primal-Dual Affine-Scaling Algorithms Fail for Semidefinite Programming.
Math. Oper. Res., 1999

1998
Affine scaling algorithm fails for semidefinite programming.
Math. Program., 1998

1996
Convergence analysis of the projective scaling algorithm based on a long-step homogeneous affine scaling algorithm.
Math. Program., 1996

An affine scaling method with an infeasible starting point: Convergence analysis under nondegeneracy assumption.
Ann. Oper. Res., 1996

1995
Global Convergence of a Long-Step Affine Scaling Algorithm for Degenerate Linear Programming Problems.
SIAM J. Optim., 1995


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