Ph.D. Thesis: Frank-Wolfe-based Boosting Algorithms and Its Extensions
I am Ryotaro Mitsuboshi, and I have a Ph. D. in Information Science.
I'm highly interested in machine learning algorithms
and their theories,
especially for boosting algorithms.
I'm continuing my research as a hobby
while I work as a Data Analyst.
Check my résumé.
Research interests
Machine Learning
Boosting
Support Vector Machines
Statistical Learning Theory
Online Learning
Convex optimization
Frank-Wolfe algorithms
Publications
Ryotaro Mitsuboshi, Kohei Hatano, and Eiji Takimoto. Online Combinatorial Linear Optimization via a Frank-Wolfe-based Metarounding Algorithm.
IEICE Transactions on Information and Systems 2024
[paper]
[arXiv]
[code]
Yuta Kurokawa, Ryotaro Mitsuboshi, Haruki Hamasaki, Kohei Hatano, Eiji Takimoto, and Holakou Rahmanian. Extended Formulations via Decision Diagrams.
COCOON 2023
[paper]
[arXiv]
[code]
[slide]
Ryotaro Mitsuboshi, Kohei Hatano, and Eiji Takimoto. Solving Linear Regression with Insensitive Loss by Boosting.
IEICE Transactions on Information and Systems 2024
[paper]
[code]
Ryotaro Mitsuboshi, Kohei Hatano, and Eiji Takimoto. Boosting as Frank-Wolfe.
Preprint
[arXiv]
[code]