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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| ET | 2024-03-03 14:35 |
Miyazaki | Miyazaki University | Development of Worker Digital Twin Generation and Visualization Function for Accident Prediction Training in Outbound Training Kaito Minohara, Toshiki Muguruma, Yusuke Kometani, Naka Gotoda, Saerom Lee, Ryo Kanda (Kagawa Univ.), Shotaro Irie, Toru Harai (Shinnihon Co.)  ET2023-72 |
In the construction industry, completing a construction project within a limited timeframe while complying with labor la... [more] | ET2023-72 pp.121-128 |
| QIT (2nd) |
2023-12-17 17:30 |
Okinawa | OIST (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Numerical computation of Bayesian Nagaoka-Hayashi bound for three-parameter qubit -state estimation Zhao Kehan, Suzuki Jun (UEC) |
In this work, we study parameter estimation about a three-parameter qubit-state model under the Bayesian setting. Recent... [more] | |
| RCS, SIP, IT | 2022-01-21 09:50 |
Online | Online | Bayesian Holevo and Nagaoka-Hayashi bounds for quantum-state estimation Jun Suzuki (UEC) IT2021-69 SIP2021-77 RCS2021-237 |
In this work we propose a Bayesian version of the Nagaoka-Hayashi bound when estimating multiple parameters for quantum ... [more] | IT2021-69 SIP2021-77 RCS2021-237 pp.231-236 |
| RCS, SIP, IT | 2022-01-21 13:55 |
Online | Online | Meta-Bound for Lower Bounds of Bayes Risk Shota Saito (Gunma Univ.) IT2021-82 SIP2021-90 RCS2021-250 |
In the parameter estimation problem of statistics and machine learning, information-theoretic lower bounds of the Bayes ... [more] | IT2021-82 SIP2021-90 RCS2021-250 pp.301-305 |
| IBISML | 2017-11-09 13:00 |
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 pp.193-200 |
| 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 |
|
| IT | 2015-07-13 15:15 |
Tokyo | Tokyo Institute of Technology | Design and Analysis of MDL Estimators for Supervised Learning Jun'ichi Takeuchi, Masanori Kawakita (Kyushu Univ.) IT2015-26 |
Barron and Coveys theory to evaluate risk bounds for the MDL estimators (1991) is basically for unsupervised learning... [more] |
IT2015-26 pp.53-58 |
| NC, IPSJ-BIO, IBISML, IPSJ-MPS (Joint) [detail] |
2015-06-23 17:00 |
Okinawa | Okinawa Institute of Science and Technology | Risk Bound of Lasso Based on MDL Theory Masanori Kawakita, Yushin Toyokihara, Jun'ichi Takeuchi (Kyushu Univ.) IBISML2015-16 |
We derive a risk bound of lasso in random design linear regression. Past works of MDL principle revealed that penalized... [more] |
IBISML2015-16 pp.101-107 |
| ISEC, IT, WBS | 2015-03-03 10:30 |
Fukuoka | The University of Kitakyushu | On Upper Bounds on Estimation Error of Least Squares Rgression with L1 Penalty Yushin Toyokihara, Masanori Kawakita, Jun'ichi Takeuchi (Kyushu Univ) IT2014-93 ISEC2014-106 WBS2014-85 |
In 1991， Barron and Cover showed for the MDL estimator that its estimation error is bounded by codelength of the corres... [more] |
IT2014-93 ISEC2014-106 WBS2014-85 pp.199-204 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2014-09-01 17:30 |
Ibaraki | Neutralized Empirical Risk Minimization with Covariance-based Neutrality Risk Kazuto Fukuchi, Jun Sakuma (Univ. of Tsukuba) PRMU2014-48 IBISML2014-29 |
In order to apply machine learning algorithms to real world problems, it is necessary to ensure that discrimination, unf... [more] | PRMU2014-48 IBISML2014-29 pp.93-100 |
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