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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 13 of 13  /   
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
 Results 1 - 13 of 13  /   
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