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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
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Committee Date Time Place Paper Title / Authors Abstract Paper #
IBISML 2022-09-15
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
IBISML 2018-03-06
Fukuoka Nishijin Plaza, Kyushu University Using local minima to accelerate Krawczyk-Hansen global optimization
Hiroaki Takada (Univ. of Tokyo), Kazuki Yoshizoe (RIKEN), Daisuke Ishii (Univ. of Fukui), Koji Tsuda (Univ. of Tokyo) IBISML2017-99
Krawczyk-Hansen algorithm employs interval calculus and branch-and-bound search to solve a global optimization problem w... [more] IBISML2017-99
IBISML 2018-03-06
Fukuoka Nishijin Plaza, Kyushu University Sonar2image: GAN-based night vision for fish monitoring
Kento Shin, Kei Terayama, Katsunori Mizuno, Koji Tsuda (Univ. of Tokyo) IBISML2017-102
Fish monitoring in an aquaculture farm is indispensable for managing fish growth and health status.
However, it is not ... [more]
IBISML 2017-11-09
Tokyo Univ. of Tokyo Fast Computation of Lower Bounds for Privacy Evaluations, Based on Binary Decision Diagrams
Shogo Takeuchi (Univ. of Tokyo), Kosuke Kusano, Jun Sakuma (Univ. of Tsukuba), Koji Tsuda (Univ. of Tokyo) IBISML2017-60
An input value estimation is a privacy issue in a service provides information by personal information. It is necessary ... [more] IBISML2017-60
IBISML 2017-03-07
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) 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
IBISML 2016-11-16
Kyoto Kyoto Univ. Selective Inference for High-Dimensional Binary Classification
Yuta Umezu, Kazuya Nakagawa (NIT), Koji Tsuda (Univ. of Tokyo), Ichiro Takeuchi (NIT) IBISML2016-59
In machine learning and other related area, the number of features is often reduced by some feature selection procedure ... [more] IBISML2016-59
PRMU, IPSJ-CVIM, IBISML [detail] 2016-09-05
Toyama   [Short Paper] Selective Inference for Time-series Change-Point Analysis
Yuta Umezu, Kazuya Nakagawa, Shigenori Inoue (NIT), Koji Tsuda (Tokyo Univ.), Mahito Sugiyama, Takuya Maekawa (Osaka Univ.), Toru Tamaki (Hiroshima Univ.), Ken Yoda (Nagoya Univ.), Ichiro Takeuchi (NIT) PRMU2016-63 IBISML2016-18
In this paper, we propose a statistical method for time series data after detecting a change point. Because the change p... [more] PRMU2016-63 IBISML2016-18
PRMU, IPSJ-CVIM, IBISML [detail] 2016-09-05
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
(Joint) [detail]
Okinawa Okinawa Institute of Science and Technology Selective inference for high-order interaction model
Shinya Suzumura, Kazuya Nakagawa (NIT), Koji Tsuda (UT), Ichiro Takeuchi (NIT) IBISML2015-11
Finding statistically significant high-order interaction features in predictive modeling is important but challenging ta... [more] IBISML2015-11
IBISML 2014-03-07
Nara Nara Women's University Online Matrix Prediction with Log-Determinant Regularizer
Kenichiro Moridomi, Kohei Hatano, Eiji Takimoto (Kyushu Univ.), Koji Tsuda (AIST) IBISML2013-75
We consider an online symmetric positive semi-definite matrix prediction problem with convex loss function and Frobenius... [more] IBISML2013-75
IBISML 2013-11-12
Tokyo Tokyo Institute of Technology, Kuramae-Kaikan [Poster Presentation] Query auditing for privacy preserving similarity search
Hiromi Arai (RIKEN), Koji Tsuda (AIST), Jun Sakuma (Univ. of Tsukuba) IBISML2013-46
In this paper, we propose a query auditing method for similarity searches that examines whether database responces satis... [more] IBISML2013-46
COMP 2013-03-18
Gifu Gifu University Compact and Fast Indices Based on Zero-Suppressed Binary Decision Diagrams
Shuhei Denzumi (Hokkaido Univ.), Jun Kawahara (NAIST), Koji Tsuda (AIST/JST), Hiroki Arimura (Hokkaido Univ.), Shin-ichi Minato (Hokkaido Univ./JST), Kunihiko Sadakane (NII) COMP2012-56
In many real-life problems, we are often faced with manipulating families of sets. Manipulation of large-scale set famil... [more] COMP2012-56
Hokkaido Hokkaido Univ. [Invited Talk] Analyzing power distribution networks by frontier-based method
Takeru Inoue (JST), Keiji Takano (Tokyo IT), Takayuki Watanabe (Waseda Univ.), Jun Kawahara (JST), Ryo Yoshinaka (Kyoto Univ.), Akihiro Kishimoto (Tokyo IT), Koji Tsuda (AIST), Shin-ichi Minato (Hokkaido Univ.), Yasuhiro Hayashi (Waseda Univ.) IN2012-39
 [more] IN2012-39
IBISML 2011-06-20
Tokyo Takeda Hall Fast Similarity Search of Binary Codes with Wavelet Tree
Yasuo Tabei (JST), Koji Tsuda (CBRC) IBISML2011-15
Similarity search using locality sensitive codes is recently of increasing interest due to unprecedented scalability. Un... [more] IBISML2011-15
IBISML 2011-03-28
Osaka Nakanoshima Center, Osaka Univ. Enumerating Feature-Sets with Submodularity
Yoshinobu Kawahara (Osaka Univ.), Koji Tsuda (AIST), Takashi Washio (Osaka Univ.), Akiko Takeda (Keio Univ.), Shin-ichi Minato (Hokkaido Univ.) IBISML2010-113
Selecting relevant features is a fundamental task in machine learning. Although many approaches have been investigated s... [more] IBISML2010-113
IBISML 2011-03-29
Osaka Nakanoshima Center, Osaka Univ. Information Geometry of Input-Output Tables
Ryoko Morioka (AIST), Koji Tsuda (AIST/JST) IBISML2010-127
A input-output (IO) table is a fundamental tool in macro economics that summarizes the transactions among industrial sec... [more] IBISML2010-127
IBISML 2010-06-14
Tokyo Takeda Hall, Univ. Tokyo [Invited Talk] All Pairs Similarity Search by Multiple Sorting
Koji Tsuda (AIST) IBISML2010-2
Recently it is increasingly common that images and signals are mapped to bit strings called sketches.
To build a simila... [more]
NC 2006-06-15
Okinawa OIST Drug-response prediction from microarray data using network-based de-noising
Tsuyoshi Kato (Univ. of Tokyo), Koh Miura, Yukio Murata (Tohoku Univ.), Kiyoshi Asai (Univ. of Tokyo), Paul B. Horton, Wataru Fujibuchi, Koji Tsuda (AIST)
Prediction of human cell response to anti-cancer drugs (compounds) from microarray data is a challenging problem, due to... [more] NC2006-16
PRMU, NLC 2005-02-24
Tokyo   Biological network inference via kernel matrix completion
Tsuyoshi Kato (AIST), Koji Tsuda (AIST/MPI for Biologcal Cybernetics), Kiyoshi Asai (Univ. of Tokyo/AIST)
Inferring networks of proteins from biological data is a central issue of computational biology. Most network inference ... [more] NLC2004-97 PRMU2004-179
 Results 1 - 19 of 19  /   
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