Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
IBISML |
2021-03-02 10:25 |
Online |
Online |
Selective Inference for Convex Clustering Using Parametric Programming Yumehiro Omori, Yu Inatsu (Nitech), Ichiro Takeuchi (Nitech/RIKEN) IBISML2020-35 |
Traditional statistical inference assumes that the hypothesis is predetermined and cannot be used as is for statistical ... [more] |
IBISML2020-35 pp.9-15 |
IBISML |
2013-11-12 15:45 |
Tokyo |
Tokyo Institute of Technology, Kuramae-Kaikan |
[Poster Presentation]
Non-Convex Optimization of Robust Support Vector Regression by Utilizing Parametric Programming Shinya Suzumura, Ichiro Takeuchi (Nagoya Inst. of Tech.), Masashi Sugiyama (Tokyo Inst. of Tech.) IBISML2013-45 |
In this paper, we propose a novel optimization method for robust support vector regression(SVR) that has robustness to o... [more] |
IBISML2013-45 pp.69-75 |
IBISML |
2013-11-13 15:45 |
Tokyo |
Tokyo Institute of Technology, Kuramae-Kaikan |
[Poster Presentation]
Learning Common Features of Parametrized Tasks Ichiro Takeuchi, Tatsuya Hongo (Nagoya Inst. of Tech.), Masashi Sugiyama (Tokyo Inst. of Tech.), Shinichi Nakajima (Nikon) IBISML2013-66 |
We introduce a novel formulation of multi-task learning (MTL) called parametric task learning (PTL) that can systematica... [more] |
IBISML2013-66 pp.225-232 |
COMP |
2013-06-24 15:10 |
Nara |
Nara Women's University |
On a parametic integer programming algorithm using dualization of monotone Boolean function Norie Fu (NII), Takafumi Shibuta (Kyushu Univ.) COMP2013-23 |
The {it parametric integer programing} is the integer programming with a vector of parameters as its right-hand-side vec... [more] |
COMP2013-23 pp.23-30 |
IBISML |
2012-11-08 15:00 |
Tokyo |
Bunkyo School Building, Tokyo Campus, Tsukuba Univ. |
Path following approach for efficient reweighted L1 minimization Yuki Shinmura, Ichiro Takeuchi (NIT) IBISML2012-71 |
The problem of recovering sparse signals is an important topic in machine learning and compressed sensing literatures.
... [more] |
IBISML2012-71 pp.265-270 |
IBISML |
2012-11-08 15:00 |
Tokyo |
Bunkyo School Building, Tokyo Campus, Tsukuba Univ. |
Multi-Instance SVM using Parametric Programming Naoki Ishihara, Saori Kurumi, Ichiro Takeuchi (NIT) IBISML2012-72 |
In this paper, we propose a new optimization algorithm for multiple instance learning (MIL). MIL is a supervised learnin... [more] |
IBISML2012-72 pp.271-276 |
IBISML |
2012-11-08 15:00 |
Tokyo |
Bunkyo School Building, Tokyo Campus, Tsukuba Univ. |
Efficient SVM Bootstrap Computation by Parametric Programming Yoshiki Suzuki, Kohei Ogawa, Ichiro Takeuchi (Nagoya Inst. of Tech.) IBISML2012-73 |
In this paper, we study statistical variability estimation of the support vector machine (SVM) by using bootstrap method... [more] |
IBISML2012-73 pp.277-282 |
IBISML |
2012-06-19 10:00 |
Kyoto |
Campus plaza Kyoto |
A study on an optimization algorithm for semi-supervised SVM using parametric programing Kohei Ogawa, Ichiro Takeuchi (NIT), Masashi Sugiyama (Tokyo Tech) IBISML2012-1 |
The goal of semi-supervised learning is to incorporate unlabeled instances as well as labeled ones for improving classif... [more] |
IBISML2012-1 pp.1-8 |
IBISML |
2011-11-10 15:45 |
Nara |
Nara Womens Univ. |
A Parametric Programming Approach for Outlier Detection and Robust Learning for Classification and Regression Ichiro Takeuchi (NIT) IBISML2011-81 |
We study outlier detection and robust learning problem for support vector machine (SVM). In the literature there are two... [more] |
IBISML2011-81 pp.263-269 |
PRMU, IBISML, IPSJ-CVIM [detail] |
2011-09-05 13:30 |
Hokkaido |
|
[Invited Talk]
Optimal Solution Path Following Algorithm for Pattern Recognition and Machine Learning Ichiro Takeuchi (NIT) PRMU2011-66 IBISML2011-25 |
Many pattern classification and machine learning algorithms are formulated as mathematical optimization problems. These ... [more] |
PRMU2011-66 IBISML2011-25 pp.59-60 |
IBISML |
2010-11-04 15:00 |
Tokyo |
IIS, Univ. of Tokyo |
[Poster Presentation]
A Study on Simultaneous Feature Selection for Cost-Sensitive Classifiers Using Mixed-Norm Regularization Toru Sugiura, Kazuaki Koide, Tatsuya Hongo, Masayuki Karasuyama, Ichiro Takeuchi (NIT) IBISML2010-70 |
Cost-sensitive learning is useful for binary classification when the
costs of miss-classifications are not symmetric. I... [more] |
IBISML2010-70 pp.83-90 |
IBISML |
2010-11-05 15:30 |
Tokyo |
IIS, Univ. of Tokyo |
[Poster Presentation]
A Study on the Suboptimal Solution Path Algorithm Masayuki Karasuyama, Ichiro Takeuchi (NIT) IBISML2010-89 |
The solution path algorithms in machine learning trace the exact optimal solutions by exploiting the piecewise linearity... [more] |
IBISML2010-89 pp.221-230 |
IBISML, PRMU, IPSJ-CVIM [detail] |
2010-09-05 17:30 |
Fukuoka |
Fukuoka Univ. |
A Study on Feature Selection Path for High-Dimensional Local Classifiers Ichiro Takeuchi (NIT) PRMU2010-71 IBISML2010-43 |
We study feature selection and weighting problems for local-based classifier. The proposed algorithm is formulated as a ... [more] |
PRMU2010-71 IBISML2010-43 pp.105-112 |