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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 46  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
SIP, IT, RCS 2024-01-18
09:30
Miyagi
(Primary: On-site, Secondary: Online)
The quantum decoding attaining the minimum guesswork with single-qubit side information
Michele Dall'Arno (TUT) IT2023-36 SIP2023-69 RCS2023-211
The minimum guesswork quantifies the minimum number of queries needed to guess the value of a random variable, when only... [more] IT2023-36 SIP2023-69 RCS2023-211
pp.37-38
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2023-06-29
13:30
Okinawa OIST Conference Center
(Primary: On-site, Secondary: Online)
Selective Inference for a Combination of Feature Selection Algorithms
Tatsuya Matsukawa (Nagoya Univ.), Daiki Miwa (NITech), Vo Nguyen Le Duy (RIKEN), Koichi Taji (Nagoya Univ.), Ichiro Takeuchi (Nagoya Univ./RIKEN) NC2023-1 IBISML2023-1
In data-driven science, classical statistical hypothesis testing does not provide an adequate reliability assessment bec... [more] NC2023-1 IBISML2023-1
pp.1-8
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2023-06-29
15:10
Okinawa OIST Conference Center
(Primary: On-site, Secondary: Online)
Selective Inference for DNN-driven Saliency Map
Daiki Miwa (NITech), Vo Nguyen Le Duy (RIKEN), Tomohiro Shiraishi (Nagoya Univ.), Ichiro Takeuchi (Nagoya Univ./RIKEN) NC2023-5 IBISML2023-5
The usefulness of image classification using DNN models has been confirmed in various fields, but the prediction mechani... [more] NC2023-5 IBISML2023-5
pp.30-34
QIT
(2nd)
2023-05-29
16:30
Kyoto Katsura Campus, Kyoto University [Poster Presentation] A parallel, branch and bound algorithm for a combinatorial instance of quantum hypothesis testing
Baasanchimed Avirmed, Kaito Niinomi, Michele Dall'Arno (Toyohashi U. of Technology)
[学生発表賞希望, application for student presentation award] We consider a particular instance of the quantum hypothesis testin... [more]
IBISML 2022-12-23
14:30
Kyoto Kyoto University
(Primary: On-site, Secondary: Online)
Selective Inference for Cluster Level Inference in Brain Image Analysis
Masaya Ikuta, Mizuki Sato (NITech), Akifumi Yamada (Nagoya Univ.), Vo Nguyen Le Duy (NITech/RIKEN), Ryo Emoto (Nagoya Univ.), Yuko Ishimaru, Yuka Takao, Atsushi Kawaguchi (Saga Univ.), Shigeyuki Matsui (Nagoya Univ.), Ichiro Takeuchi (Nagoya Univ./RIKEN) IBISML2022-61
Cluster-level inference in brain image analysis is often employed to identify disease-related regions in brain disorders... [more] IBISML2022-61
pp.128-133
IT, EMM 2022-05-18
12:40
Gifu Gifu University
(Primary: On-site, Secondary: Online)
On Bayesian Approach for Classification of Context Tree Model
Shota Saito (Gunma Univ.) IT2022-11 EMM2022-11
This study deals with the Bayesian classification problem, which was investigated by Merhav and Ziv [IEEE Trans. Inf. Th... [more] IT2022-11 EMM2022-11
pp.56-60
IT, ISEC, RCC, WBS 2022-03-11
14:55
Online Online On Strong Converse Theorem for Distributed Hypothesis Testing
Yasutada Oohama (UEC) IT2021-122 ISEC2021-87 WBS2021-90 RCC2021-97
In this study, we consider a communication system in which data
generated at two points with correlation is separatley... [more]
IT2021-122 ISEC2021-87 WBS2021-90 RCC2021-97
pp.228-233
WBS, IT, ISEC 2021-03-05
14:45
Online Online Analysis of Optimal Error Exponents on Classification for Markov Sources
Hiroto Kuramata, Hideki Yagi, Tsutomu Kawabata (UEC) IT2020-152 ISEC2020-82 WBS2020-71
We consider a classification problem for a test sequence to determine from which source the sequence generates. The syst... [more] IT2020-152 ISEC2020-82 WBS2020-71
pp.245-250
SIP, IT, RCS 2021-01-21
15:45
Online Online [Special Invited Talk] Turbo Equalization to Lossless/Lossy Distributed Multiterminal Source Coding: How are they connected? -- Towards Distributed Hypothesis Testing over IoT Networks --
Tadashi Matsumoto (JAIST) IT2020-80 SIP2020-58 RCS2020-171
A goal of this talk is to provide the audience with the knowledge about how the presenter's research experiences and foo... [more] IT2020-80 SIP2020-58 RCS2020-171
p.99
IT 2020-12-02
10:30
Online Online Error Probability of Classification Based on the Analysis of the Bayes Code -- Extension and Example --
Shota Saito, Toshiyasu Matsushima (Waseda Univ.) IT2020-32
Suppose that we have two training sequences generated by parametrized distributions $P_{theta^*}$ and $P_{xi^*}$, where ... [more] IT2020-32
pp.44-49
IBISML 2020-10-22
09:05
Online Online IBISML2020-26 A new selective inference approach via multiscale bootstrap is proposed for general hypotheses conditioned on complicate... [more] IBISML2020-26
p.45
SR 2019-12-06
13:00
Okinawa Ishigaki City Hall (Ishigaki Island) Radio Environment Map Updating Procedure based on Hypothesis Testing
Keita Katagiri, Takeo Fujii (UEC) SR2019-104
(To be available after the conference date) [more] SR2019-104
pp.87-94
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
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
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 2017-11-09
13:00
Tokyo Univ. of Tokyo [Poster Presentation] Learning huge Bayesian networks using RAI algorithm based on Bayes factor
Kazuki Natori, Masaki Uto, Maomi Ueno (UEC) IBISML2017-58
``Learning Bayesian networks'' has NP-hard problem. The state-of-the-arts method of learning Bayesian networks cannot le... [more] IBISML2017-58
pp.177-184
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 2017-11-10
13:00
Tokyo Univ. of Tokyo [Poster Presentation] Correcting selection bias in active learning based on selective inference framework
Yu Inatsu (RIKEN), Ichiro Takeuchi (Nitech/RIKEN/NIMS) IBISML2017-74
Consider the active learning that constructs regression model from given data and actually observes the value at the po... [more] IBISML2017-74
pp.289-296
MBE, NC
(Joint)
2016-12-07
13:55
Aichi Toyohashi University of Technology A Study of the System to Control Static Upright Posture of Humans
Jono Yusuke, Takada Hiroki (Fukui Univ) MBE2016-62
Humans spend most of their everyday life in standing position. If it were difficult to maintain an upright posture, we w... [more] MBE2016-62
pp.31-34
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