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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 9 of 9  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
MI 2024-03-03
09:17
Okinawa OKINAWAKEN SEINENKAIKAN
(Primary: On-site, Secondary: Online)
[Short Paper] Valid p-value for critical instances in multiple instance learning
Noriaki Hashimoto (RIKEN), Daiki Miwa (Nitech), Kosei Sumida (Nagoya Univ.), Hiroyuki Hanada (RIKEN), Hiroaki Miyoshi (Kurume Univ.), Jun Sakuma (Tokyo Tech/RIKEN), Hidekata Hontani (Nitech), Koichi Ohshima (Kurume Univ.), Ichiro Takeuchi (Nagoya Univ./RIKEN) MI2023-31
(To be available after the conference date) [more] MI2023-31
pp.3-6
PRMU, IBISML, IPSJ-CVIM [detail] 2023-03-03
16:25
Hokkaido Future University Hakodate
(Primary: On-site, Secondary: Online)
Fast Identification of Possible Model Parameter Update for Low-Rank Update of Training Data
Hiroyuki Hanada, Noriaki Hashimoto (RIKEN), Kouichi Taji, Ichiro Takeuchi (Nagoya Univ.) PRMU2022-123 IBISML2022-130
Machine learning methods often require re-training the training dataset with low-rank modifications (small number of ins... [more] PRMU2022-123 IBISML2022-130
pp.347-354
IBISML 2022-09-15
15:05
Kanagawa Keio Univ. (Yagami Campus)
(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
MI 2022-07-08
14:00
Hokkaido
(Primary: On-site, Secondary: Online)
Cell type-specific tumor degree estimation in malignant lymphoma pathology images
Hiroki Masuda (NITech), Noriaki Hashimoto (RIKEN), Yusuke Takagi (NITech), Hiroyuki Hanada (RIKEN), Hiroaki Miyoshi, Kensaku Sato, Koichi Oshima (Kurume Univ.), Hidekata Hontani (NITech), Ichiro Takeuchi (Nagoya Univ./RIKEN) MI2022-32
In the pathological diagnosis flow of malignant lymphoma, a type of blood cancer, it is important to identify the type o... [more] MI2022-32
pp.1-6
IBISML 2018-03-06
10:00
Fukuoka Nishijin Plaza, Kyushu University 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 2016-11-17
14:00
Kyoto Kyoto Univ. Empirical risk minimization for interval data and its applications to privacy preservations
Hiroyuki Hanada, Toshiyuki Takada, Atsushi Shibagaki (NITech), Jun Sakuma (Univ. of Tsukuba), Ichiro Takeuchi (NITech) IBISML2016-89
In this research, for machine learning tasks, we consider that the values in the training data are given as intervals an... [more] IBISML2016-89
pp.305-312
PRMU, IPSJ-CVIM, IBISML [detail] 2016-09-06
10:45
Toyama   A proposal on quick sensitivity analysis of empirical risk minimization problems
Hiroyuki Hanada, Atsushi Shibagaki (NITech), Jun Sakuma (Univ. of Tsukuba), Ichiro Takeuchi (NITech) PRMU2016-80 IBISML2016-35
For a training data set consisting of $n$ vectors of $d$ dimensions, we consider obtaining a training result from it by ... [more] PRMU2016-80 IBISML2016-35
pp.203-210
IBISML 2015-11-27
14:00
Ibaraki Epochal Tsukuba [Poster Presentation] Secure Approximation Guarantee for Private Empirical Risk Minimization with Homomorphic Encryption
Toshiyuki Takada, Hiroyuki Hanada (NIT), Jun Sakuma (Univ.Tsukuba), Ichiro takeuchi (NIT) IBISML2015-86
Privacy concern has been increasingly important in many machine learning problems. In this paper, we study empirical ris... [more] IBISML2015-86
pp.249-256
PRMU, DE 2008-06-19
14:00
Hokkaido Otaru-Shimin-Kaikan A study on fast search of the nearest string in edit distance
Hiroyuki Hanada, Mineichi Kudo (Hokkaido Univ.) DE2008-8 PRMU2008-26
The problem is finding the nearest string, measured by edit distance,
to a query string $q$ from a set $T$ of strings. ... [more]
DE2008-8 PRMU2008-26
pp.41-46
 Results 1 - 9 of 9  /   
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