| IEICE Technical Committee Submission System Conference Schedule |
Online Proceedings [Sign in] Tech. Rep. Archives |
All Technical Committee Conferences (All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IBISML | 2022-01-17 11:20 |
Online | Online | CAMRI Loss: Class-wise Additive Angular Margin Loss for Improving Recall of a Specific Class Daiki Nishiyama (Univ. Tsukuba), Fukuchi Kazuto, Yohei Akimoto, Jun Sakuma (Univ. Tsukuba/RIKEN)  IBISML2021-22 |
In real-world applications of multiclass classification models, there is a need to increase the recall of classes where ... [more] | IBISML2021-22 pp.29-36 |
| IBISML | 2022-01-18 13:20 |
Online | Online | IBISML2021-24 |
We aim to explain a black-box classifier with the form: `data X is classified as class Y because X has A, B and does not... [more] | IBISML2021-24 pp.45-53 |
| IBISML | 2020-10-22 14:50 |
Online | Online | Suppressing explanations with irrelevant concepts in deep learning Munemasa Tomohiro (Tsukuba Univ), Fukuchi Kazuto, Akimoto Yohei, Sakuma Jun (Tsukuba Univ/Riken AIP) IBISML2020-32 |
TCAV [1], which is an explanation method using a concept that humans easily understand for deep learning models, concept... [more] | IBISML2020-32 pp.61-68 |
| IBISML | 2017-11-09 13:00 |
Tokyo | Univ. of Tokyo | Online Optimization Method for Generalized $ell_1$ Regularized Problems Yoshihiro Nakazato, Kazuto Fukuchi (Tsukuba Univ.), Jun Sakuma (Tsukuba Univ./Riken/JST) IBISML2017-47 |
Structured sparse regularization is vital to enhance the precision and the interpretability of the model by introducing ... [more] | IBISML2017-47 pp.93-100 |
| IBISML | 2017-11-09 13:00 |
Tokyo | Univ. of Tokyo | Consequently Fair Contextual Bandit Learning Kazuto Fukuchi (Univ. of Tsukuba), Jun Sakuma (Univ. of Tsukuba/JST/RIKEN) IBISML2017-53 |
Fairness in machine learning is being recognized as an important field. It requires that the consequent decisions made b... [more] | IBISML2017-53 pp.139-146 |
| IBISML | 2016-11-16 15:00 |
Kyoto | Kyoto Univ. | Proximal Average Accelerated Proximal Gradient Algorithm with Adaptive Restart Yoshihiro Nakazato, Kazuto Fukuchi, Jun Sakuma (Univ. Tsukuba) IBISML2016-55 |
When using multiple regularizers, their proximal mapping is not easily available in closed form. The method to calculat... [more] |
IBISML2016-55 pp.65-71 |
| IBISML | 2016-11-17 14:00 |
Kyoto | Kyoto Univ. | Minimax optimal estimator for additively decomposable scalar functionals of discrete distributions Kazuto Fukuchi, Jun Sakuma (Univ. of Tsukuba) IBISML2016-82 |
We deal with a problem of estimating additively decomposable scalar functionals from a set of $n$ iid samples drawn from... [more] | IBISML2016-82 pp.259-265 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Differential Privacy on Linear Regression Model of Crowdsensing Tran Quang Khai, Kazuto Fukuchi, Jun Sakuma (Univ. of Tsukuba) IBISML2014-47 |
Learning statistic models using the data collected from crowd is one of the important tasks in the crowdsensing. Crowdse... [more] | IBISML2014-47 pp.95-102 |
| 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 |
|
[Return to Top Page]