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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | [Poster Presentation]
Selective Inference for Feature Selection after Hierarchical Clustering Kenta Suzuki, Shigenori Inoue, Yuta Umezu (NIT), Ichiro Takeuchi (NIT/NIMS/RIKEN)  IBISML2018-70 |
It is important to find characteristic features behind the data from, e.g., gene expression level or customer's purchase... [more] | IBISML2018-70 pp.197-204 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | [Poster Presentation]
Selective Inference for Dynamic Programming-based Sequence Segmentation Hiroki Toda, Yuta Umezu, Takuto Sakuma (NIT), Ichiro Takeuchi (NIT/NIMS/RIKEN) IBISML2018-81 |
Recently, a large number of sensor devices have enabled us to collect various kind of sequence data easily. Sequence seg... [more] | IBISML2018-81 pp.279-286 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | [Poster Presentation]
Active Learning in Sparse Linear Regression Models via Selective Inference Yuta Umezu (NIT), Ichiro Takeuchi (NIT/NIMS/RIKEN) IBISML2018-95 |
In order to efficiently estimate interested parameter, one can design sampling strategy by defining some criterion on th... [more] | IBISML2018-95 pp.381-388 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2018-06-13 10:50 |
Okinawa | Okinawa Institute of Science and Technology | Post Clustering Inference, with Application to Single Cell Analysis Shigenori Inoue, Yuta Umezu (NIT), Shouma Tsubota (Nagoya Univ.), Ichiro Takeuchi (NIT/RIKEN/NIMS) IBISML2018-3 |
There are many data with several subgroups, such as customer data and gene expression data and so on. One way to analyze... [more] | IBISML2018-3 pp.15-22 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2018-06-13 11:15 |
Okinawa | Okinawa Institute of Science and Technology | Selective Inference for Predictive Sequence Mining and Its Applications to Trajectory Data Analysis Kazuya Nishi, Takuto Sakuma, Yuta Umezu, Shinsuke Kajioka, Ichiro Takeuchi (NIT) IBISML2018-4 |
[more] | IBISML2018-4 pp.23-29 |
| IBISML | 2017-11-09 13:00 |
Tokyo | Univ. of Tokyo | [Poster Presentation]
Post Clustering Inference for Heterogeneous Data Shigenori Inoue, Yuta Umezu (NIT), Shoma Tsubota (Nagoya Univ.), Ichiro Takeuchi (NIT/RIKEN/NIMS) IBISML2017-44 |
Along with the prevalence of Precision Medicine, the demand for analytical methods on heterogeneous data is increasing. ... [more] | IBISML2017-44 pp.69-76 |
| IBISML | 2017-11-10 13:00 |
Tokyo | Univ. of Tokyo | [Poster Presentation]
Selective Inference for Change Point Detection in Multidimensional Sequence Yuta Umezu (Nitech), Ichiro Takeuchi (Nitech/RIKEN/NIMS) IBISML2017-71 |
In various fields such as engineering, bioinformatics and econometrics, detecting structural changes from a given sequen... [more] | IBISML2017-71 pp.269-276 |
| 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) 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 |
| IBISML | 2016-11-16 15:00 |
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 pp.93-100 |
| PRMU, IPSJ-CVIM, IBISML [detail] | 2016-09-05 13:15 |
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 pp.89-92 |
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