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Search Results: Conference Papers
 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 26件中 1~20件目  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] 2019-06-17
17:00
Okinawa Okinawa Institute of Science and Technology Adaptive Discretization based Predictive Sequence Mining for Continuous Time Series
Yoshikazu Shibahara, Takuto Sakuma (NIT), Ichiro Takeuchi (NIT/RIKEN/NIMS), Masayuki Karasuyama (NIT/NIMS)
In recent years, improvement of sensor performance and spread of portable devices such as smartphones enable us to easil... [more] IBISML2019-9
pp.57-64
IBISML 2018-11-05
15:10
Hokkaido Hokkaido Citizens Activites Center (Kaderu 2.7) [Poster Presentation] Distance Metric Learning Between Graphs Based on Subgraph
Tomoki Yoshida (NITech), Ichiro Takeuchi (NITech/NIMS/RIKEN), Masayuki Karasuyama (NITech/NIMS/JST)
A standard approach to evaluating distance between two graphs is to use common subgraphs contained in the two graphs. Fo... [more] IBISML2018-64
pp.151-158
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2018-06-13
10:00
Okinawa Okinawa Institute of Science and Technology Active Level Set Estimation with Multi-fidelity Evaluations
Shion Takeno (Nitech), Hitoshi Fukuoka (Nagoya Univ.), Yuhki Tsukada (Nagoya Univ./JST), Toshiyuki Koyama (Nagoya Univ.), Motoki Shiga (Gifu Univ./JST/RIKEN), Ichiro Takeuchi (NITech/NIMS/RIKEN), Masayuki Karasuyama (NITech/NIMS/JST)
Level set estimation is a problem to identify a level set of an unknown function, which is defined by whether the functi... [more] IBISML2018-1
pp.1-8
IBISML 2018-03-06
11:15
Fukuoka Nishijin Plaza, Kyushu University Selecting discriminative and representative patterns from sequence data: an approach based on classification model and morse complex
Masayuki Karasuyama (Nagoya Inst. of Tech./NIMS/JST), Ichiro Takeuchi (Nagoya Inst. of Tech./NIMS/RIKEN)
We study classification problem on the sequences of continuous observations. In particular, we are interested in identif... [more] IBISML2017-101
pp.77-84
IBISML 2017-11-10
13:00
Tokyo Univ. of Tokyo Safe Screening for Large Margin Metric Learning
Tomoki Yoshida (NITech), Ichiro Takeuchi (NITech/NIMS/RIKEN), Masayuki Karasuyama (NITech/NIMS/JST)
Large margin metric learning learns the optimal Mahalanobis distance for classification problem based on the margin maxi... [more] IBISML2017-64
pp.219-226
NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] 2017-06-25
11:25
Okinawa Okinawa Institute of Science and Technology Cost-sensitive Bayesian optimization for multiple objectives and its application to material science
Tomohiro Yonezu (NITech), Tomoyuki Tamura, Ryo Kobayashi (NITech/NIMS), Ichiro Takeuchi (NITech/NIMS/RIKEN), Masayuki Karasuyama (NITech/NIMS/JST)
We consider solving a set of black-box optimization problems in which each problem has a similar objective function each... [more] IBISML2017-10
pp.207-213
IBISML 2017-03-07
10:00
Tokyo Tokyo Institute of Technology Safe Pruning Rule for Predictive Sequential Pattern Mining and Its Application to Bio-logging Data Analysis
Kaoru Kishimoto (NITech), Masayuki Karasuyama (NIT), Kazuya Nakagawa (NITech), Kotaro Kimura (Osaka Univ.), Ken Yoda (Nagoya Univ.), Yuta Umezu, Shinsuke Kajioka (NITech), Koji Tsuda (UTokyo), Ichiro Takeuchi (NITech)
Recently, the analysis for time-series logging data of animal behaviors, called bio-logging data, has attracted a wide a... [more] IBISML2016-105
pp.41-48
IBISML 2017-03-07
11:00
Tokyo Tokyo Institute of Technology A study on minimizing size of sparse model optimization problem: exploiting safe rules for keeping and removing variables
Masayuki Karasuyama (NIT/NIMS/JST), Atsushi Shibagaki (NIT), Ichiro Takeuchi (NIT/NIMS/RIKEN/NIMS)
 [more] IBISML2016-107
pp.57-62
IBISML 2016-11-16
15:00
Kyoto Kyoto Univ. Exploring GB Energies using Gaussian Process
Masayuki Karasuyama (NIT/NIMS/JST Sakigake), Tomoyuki Tamura, Ryo Kobayashi, Ichiro Takeuchi, Masanobu Nakayama (NIT/NIMS)
 [more] IBISML2016-67
pp.151-154
IBISML 2016-11-17
14:00
Kyoto Kyoto Univ. [Poster Presentation] Estimating Proton Conductivity in Crystals by using Guassian Process and Dynamic Programming
Kenta Kanamori (NITech), Kazuaki Toyoura (Kyoto Univ.), Shinichi Nakajima (TU Berlin), Atsuto Seko (Kyoto Univ.), Masayuki Karasuyama (NITech), Akihide Kuwabara (JFCC), Junya Honda (Tokyo Univ.), Kazuki Shitara (JFCC), Motoki Shiga (Gifu Univ.), Ichiro Takeuchi (NITech)
In material science, $proton conductivity$ is very important property for designing new battery and it is defined as max... [more] IBISML2016-73
pp.191-198
PRMU, IPSJ-CVIM, IBISML [detail] 2016-09-05
15:45
Toyama   Sparse learning for pattern mining problem by using Safe Pattern Pruning method
Kazuya Nakagawa, Shinya Suzumura, Masayuki Karasuyama (NIT), Koji Tsuda (Univ. of Tokyo), Ichiro Takeuchi (NIT)
In this paper we study predictive pattern mining problems where the goal is to construct a predictive model based on a s... [more] PRMU2016-70 IBISML2016-25
pp.127-134
NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] 2016-07-06
10:50
Okinawa Okinawa Institute of Science and Technology Simultaneous Safe Screening of Features and Samples in Doubly Sparse Modeling
Atsushi Shibagaki, Masayuki Karasuyama (NIT), Kohei Hatano (Kyushu Univ.), Ichiro Takeuchi (NIT)
 [more] IBISML2016-4
pp.201-208
IBISML 2015-11-26
15:00
Ibaraki Epochal Tsukuba [Poster Presentation] Selective sampling by using Gaussian Process and its application to material science
Daisuke Hirano (NIT), Kazuaki Toyoura (Nagoya Univ.), Atsuto Seko (Kyoto Univ.), Motoki Shiga (Gifu Univ.), Akihide Kuwabara (JFCC), Masayuki Karasuyama (NIT), Kazuki Shitara (Kyoto Univ.), Ichiro Takeuchi (NIT)
Various physical phenomena and properties of an unknown material are often revealed by exhaustively evaluating the entir... [more] IBISML2015-66
pp.99-106
IBISML 2015-11-27
14:00
Ibaraki Epochal Tsukuba [Poster Presentation] Clustering Features based on Simultaneous Manifold Learning
Masayuki Karasuyama (NIT), Hiroshi Mamitsuka (Kyoto Univ.)
 [more] IBISML2015-79
pp.195-201
NC, IPSJ-BIO, IBISML, IPSJ-MPS
(Joint) [detail]
2015-06-23
14:15
Okinawa Okinawa Institute of Science and Technology Efficient sparse learning for combinatorial model by using safe screening approach
Kazuya Nakagawa, Shinya Suzumura, Masayuki Karasuyama, Ichiro Takeuchi (NIT)
In a variety of machine learning tasks, it has been desired to incorporate high-order interaction effects of multiple co... [more] IBISML2015-10
pp.63-68
IBISML 2013-03-05
16:30
Aichi Nagoya Institute of Technology Similarity adaptation for label propagation based on local linear reconstruction
Masayuki Karasuyama, Hiroshi Mamitsuka (Kyoto Univ.)
Label propagation is one of the state-of-the-art methods for semi-supervised
learning,
which estimates labels by pro... [more]
IBISML2012-109
pp.115-121
IBISML 2012-11-07
15:30
Tokyo Bunkyo School Building, Tokyo Campus, Tsukuba Univ. Propagating Labels via Sparse Combination of Multiple Graphs
Masayuki Karasuyama, Hiroshi Mamitsuka (Kyoto Univ.)
Label propagation is a widely accepted approach in graph-based
semi-supervised learning that predicts labels of nodes ... [more]
IBISML2012-58
pp.171-178
PRMU, IBISML, IPSJ-CVIM [detail] 2011-09-06
15:50
Hokkaido   Canonical Dependency Analysis based on Squared-loss Mutual Information
Masayuki Karasuyama, Masashi Sugiyama (Tokyo Inst. of Tech.)
Canonical correlation analysis (CCA) is a classical technique to iteratively find projection directions for two sets of ... [more] PRMU2011-79 IBISML2011-38
pp.173-180
IBISML 2011-03-28
15:00
Osaka Nakanoshima Center, Osaka Univ. A Study on Position-based Adaptive Weighting for Ranking SVM
Masayuki Karasuyama, Takuya Hasegawa, Tsukasa Matsuno, Ichiro Takeuchi (Nagoya Inst. of Tech.)
This paper presents a novel training algorithm for ranking support vector machine (ranking SVM). The focus is on how to ... [more] IBISML2010-115
pp.77-83
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)
Cost-sensitive learning is useful for binary classification when the
costs of miss-classifications are not symmetric. I... [more]
IBISML2010-70
pp.83-90
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