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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 35  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2023-06-29
Okinawa OIST Conference Center
(Primary: On-site, Secondary: Online)
Crystal structure X-ray absorption spectrum prediction and valence ratio estimation based on Gaussian process regression
Takumi Iwashita, Haruki Hirai, Ryo Kobayashi, Tomoyuki Tamura, Masayuki Karasuyama (NIT) NC2023-3 IBISML2023-3
X-ray absorption spectra are known as a useful experimental measurement technique for crystal structure analysis. Spectr... [more] NC2023-3 IBISML2023-3
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2023-06-30
Okinawa OIST Conference Center
(Primary: On-site, Secondary: Online)
Predictive graph mining for attributed graph data through proximal gradient pruning
Ren Sugihara, Shinji Tajima, Ryota Kitahara, Masayuki Karasuyama (NIT) NC2023-16 IBISML2023-16
 [more] NC2023-16 IBISML2023-16
IBISML 2022-12-23
Kyoto Kyoto University
(Primary: On-site, Secondary: Online)
IBISML2022-60 (To be available after the conference date) [more] IBISML2022-60
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 2022-01-17
Online Online Constrained Bayesian Optimization through Optimal-value Entropy
Shion Takeno, Tomoyuki Tamura (NIT), Kazuki Shitara (Osaka Univ./JFCC), Masayuki Karasuyama (NIT) IBISML2021-19
The constrained optimization problem for the expensive black-box function is a major problem. Although the effectiveness... [more] IBISML2021-19
IBISML 2022-01-18
Online Online Local Explanation of Graph Neural Network through Predictive Graph Mining
Hinata Asahi, Masayuki Karasuyama (NIT) IBISML2021-23
Graph Neural Networks (GNNs) have attracted wide attention in the data science community. However, predictions of GNNs a... [more] IBISML2021-23
IBISML 2022-01-18
Online Online Bayesian Optimization for Simultaneous Optimization of Multiple Tasks with Max-value Entropy Search
Rintaro Yamada, Shion Takeno, Masayuki Karasuyama (NIT) IBISML2021-28
Bayesian optimization (BO) has been widely studied as an effective approach to black-box optimizations. On the other han... [more] IBISML2021-28
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2021-06-28
Online Online Predictive Graph Mining using Graphs with Interval Attributes
Hinata Asahi, Masayuki Karasuyama (NIT) NC2021-6 IBISML2021-6
Graphs have been widely used to represent structured data such as molecular data and traffic networks. In this paper, we... [more] NC2021-6 IBISML2021-6
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2021-06-28
Online Online Active learning for distributionally robust chance-constrained optimization
Yu Inatsu, Shion Takeno, Masayuki Karasuyama (Nitech), Ichiro Takeuchi (Nitech/RIKEN) NC2021-7 IBISML2021-7
Chance-constrained optimization (CCO) is one of the constrained optimization problems where some of the inputs to a blac... [more] NC2021-7 IBISML2021-7
NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] 2019-06-17
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) IBISML2019-9
In recent years, improvement of sensor performance and spread of portable devices such as smartphones enable us to easil... [more] IBISML2019-9
IBISML 2018-11-05
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) IBISML2018-64
A standard approach to evaluating distance between two graphs is to use common subgraphs contained in the two graphs. Fo... [more] IBISML2018-64
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2018-06-13
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) IBISML2018-1
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
IBISML 2018-03-06
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) IBISML2017-101
We study classification problem on the sequences of continuous observations. In particular, we are interested in identif... [more] IBISML2017-101
IBISML 2017-11-10
Tokyo Univ. of 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
NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] 2017-06-25
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) IBISML2017-10
We consider solving a set of black-box optimization problems in which each problem has a similar objective function each... [more] IBISML2017-10
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 2017-03-07
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) IBISML2016-107
 [more] IBISML2016-107
IBISML 2016-11-16
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) IBISML2016-67
 [more] IBISML2016-67
IBISML 2016-11-17
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) IBISML2016-73
In material science, $proton conductivity$ is very important property for designing new battery and it is defined as max... [more] IBISML2016-73
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
 Results 1 - 20 of 35  /  [Next]  
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