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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 8 of 8  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
IBISML, NC, IPSJ-BIO, IPSJ-MPS [detail] 2024-06-20
15:50
Okinawa OIST (Okinawa) Distributionally Robust Safe Sample Screening and Its Application to Infinite-width Deep Neural Networks
Tatsuya Aoyama (Nagoya Univ.), Hiroyuki Hanada (RIKEN), Satoshi Akahane, Yoshito Okura, Tomonari Tanaka (Nagoya Univ.), Yu Inatsu (NITech), Noriaki Hashimoto (RIKEN), Taro Murayama, Lee Hanju, Shinya Kojima (DENSO), Ichiro Takeuchi (Nagoya Univ.) NC2024-10 IBISML2024-10
In machine learning, handling large datasets has been problematic in computational resources. For this issue, safe sampl... [more] NC2024-10 IBISML2024-10
pp.67-72
IBISML 2022-09-15
15:05
Kanagawa Keio Univ. (Yagami Campus) (Kanagawa, Online)
(Primary: On-site, Secondary: Online)
Improving Efficiency of Regularization Path Computation in Safe Pattern Pruning via Multiple Referential Solutions
Takumi Yoshida (Nitech), Hiroyuki Hanada (RIKEN), Kazuya Nakagawa, Shinya Suzumura, Onur Boyar, Kazuki Iwata (Nitech), Shun Shimura, Yuji Tanaka (NaogyaU), Masayuki Karasuyama (Nitech), Kouichi Taji (NaogyaU), Koji Tsuda (UTokyo/RIKEN), Ichiro Takeuchi (NaogyaU/RIKEN) IBISML2022-38
Safe Screening and Safe Pattern Pruning are methods for efficiently modeling high-dimensional features by $L_1$-regulari... [more] IBISML2022-38
pp.39-46
IBISML 2018-11-05
15:10
Hokkaido Hokkaido Citizens Activites Center (Kaderu 2.7) (Hokkaido) [Poster Presentation] Safe Screening of a Sparse KLIEP Model on Markov Network Structural Change Detection
Hiroki Sato (Gifu Univ), Motoki Shiga (Gifu Univ./JST/RIKEN), Makoto Yamada (Kyoto Univ./JST/RIKEN) IBISML2018-52
On gene network analysis, detecting network structural changes among different cell states is necessary to understand bi... [more] IBISML2018-52
pp.61-68
IBISML 2018-03-06
10:00
Fukuoka Nishijin Plaza, Kyushu University (Fukuoka) Learning rule-base model by Safe Pattern Pruning
Hiroki Kato, Hiroyuki Hanada (Nagoya Inst. of Tech.), Ichiro Takeuchi (Nagoya Inst. of Tech./RIKEN/NIMS) IBISML2017-98
We consider learning the prediction model called ''rule-base model''. Rule-base model is the model which uses ''rules'' ... [more] IBISML2017-98
pp.55-62
IBISML 2017-11-10
13:00
Tokyo Univ. of Tokyo (Tokyo) Safe Screening for Large Margin Metric Learning
Tomoki Yoshida (NITech), Ichiro Takeuchi (NITech/NIMS/RIKEN), Masayuki Karasuyama (NITech/NIMS/JST) IBISML2017-64
Large margin metric learning learns the optimal Mahalanobis distance for classification problem based on the margin maxi... [more] IBISML2017-64
pp.219-226
IBISML 2017-03-07
10:00
Tokyo Tokyo Institute of Technology (Tokyo) 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) IBISML2016-105
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
PRMU, IPSJ-CVIM, IBISML [detail] 2016-09-05
15:45
Toyama (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) PRMU2016-70 IBISML2016-25
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
(Joint) [detail]
2015-06-23
14:15
Okinawa Okinawa Institute of Science and Technology (Okinawa) Efficient sparse learning for combinatorial model by using safe screening approach
Kazuya Nakagawa, Shinya Suzumura, Masayuki Karasuyama, Ichiro Takeuchi (NIT) IBISML2015-10
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
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