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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IBISML | 2020-03-11 11:10 |
Kyoto | Kyoto University (Cancelled but technical report was issued) |
Multi-cross Hinge Loss for Unbalanced Multi-class Classification Shumpei Kurora (Wakayama Univ), Hirotaka Hachiya (Wakayama Univ/RIKEN), Udai Shimada (MRI), Naonori Ueda (RIKEN)  IBISML2019-44 |
[more] | IBISML2019-44 pp.79-84 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | [Poster Presentation]
Crowd Navigation via Bayesian Optimization of Multi-agent Simulation Hitoshi Shimizu, Takuma Otsuka, Tomoharu Iwata, Hiroshi Sawada, Futoshi Naya, Naonori Ueda (NTT) IBISML2018-57 |
In a large event where a large number of people gather, to prepare plans for safely guiding visitors in advance, predict... [more] | IBISML2018-57 pp.99-104 |
| NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] | 2016-07-06 10:25 |
Okinawa | Okinawa Institute of Science and Technology | A Semi-supervised Learning Method for Imbalanced Binary Classification Akinori Fujino, Naonori Ueda (NTT) IBISML2016-3 |
This paper presents a semi-supervised learning method for imbalanced binary classification where the number of positive ... [more] | IBISML2016-3 pp.195-200 |
| IBISML | 2015-03-06 11:00 |
Kyoto | Kyoto University | Asymptotic Properties of Area Under the ROC Curve via Likelihood Ratio Based Ranking Function Kentaro Nakanishi, Toshiyuki Tanaka (Kyoto Univ.), Naonori Ueda (NTT) IBISML2014-92 |
We study properties of the area under the ROC curve, which is one of measures to evaluate performance of a binary classi... [more] | IBISML2014-92 pp.55-62 |
| IBISML | 2014-11-18 15:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Infinitely exchangeable rectangular partitioning Masahiro Nakano, Katsuhiko Ishiguro, Akisato Kimura, Takeshi Yamada, Naonori Ueda (NTT) IBISML2014-77 |
(Advance abstract in Japanese is available) [more] | IBISML2014-77 pp.313-320 |
| IBISML | 2013-11-13 15:45 |
Tokyo | Tokyo Institute of Technology, Kuramae-Kaikan | [Poster Presentation]
Floor-plan partitioning stochastic processes for relational data analysis Masahiro Nakano, Katsuhiko Ishiguro, Akisato Kimura, Takeshi Yamada, Naonori Ueda (NTT) IBISML2013-62 |
This paper presents a floor-plan partitioning stochastic process, that can potentially generate arbitrary rectangular pa... [more] | IBISML2013-62 pp.197-204 |
| IBISML | 2012-11-07 15:30 |
Tokyo | Bunkyo School Building, Tokyo Campus, Tsukuba Univ. | Subset Infinite Relational Model Katsuhiko Ishiguro, Naonori Ueda, Hiroshi Sawada (NTT) IBISML2012-37 |
We propose a new probabilistic generative model for analyzing sparse and noisy relational data, such as friend-links on ... [more] | IBISML2012-37 pp.23-30 |
| IBISML | 2012-03-12 10:50 |
Tokyo | The Institute of Statistical Mathematics | Detecting Latent Structural Changes via Latent Dirichlet Allocation Masashi Ueda, Ryota Tomioka, Kenji Yamanishi (The Univ. of Tokyo), Katsuhiko Ishiguro, Hiroshi Sawada, Naonori Ueda (NTT) IBISML2011-89 |
Detecting changes in consumers' latent preference is a fundamental challenge for improving recommendation systems as wel... [more] | IBISML2011-89 pp.15-20 |
| NC, MBE (Joint) |
2010-03-09 11:05 |
Tokyo | Tamagawa University | Related Abstract Search Tool:RAST Nilton Liuji Kamiji (RIKEN), Tatsuki Taniguchi (IVIS), Naonori Ueda (NTT Comm Sci Labs.), Shiro Usui (RIKEN) NC2009-91 |
With the increasing amount of information available in recent years, searching for the desired content is becoming a cha... [more] | NC2009-91 pp.23-28 |
| AI | 2009-05-22 11:00 |
Tokyo | Unsupervised extraction of content-related annotations Tomoharu Iwata, Takeshi Yamada, Naonori Ueda (NTT) AI2009-3 |
(To be available after the conference date) [more] | AI2009-3 pp.13-18 |
|
| PRMU | 2009-03-13 13:25 |
Miyagi | Tohoku Institute of Technology | [Special Talk]
none Naonori Ueda (NTT) PRMU2008-248 |
[more] | PRMU2008-248 pp.55-60 |
| PRMU, DE | 2007-06-29 13:30 |
Hokkaido | Hokkaido Univ. | Graph Clustering with a Nonparametric Bayes Model Shuhei Kuwata, Naonori Ueda, Takeshi Yamada (NTT) DE2007-15 PRMU2007-41 |
We propose a new graph clustering method based on a nonparametric Bayesian model. Recently, Newman et al. proposed an ef... [more] | DE2007-15 PRMU2007-41 pp.81-86 |
| PRMU, DE | 2007-06-29 14:00 |
Hokkaido | Hokkaido Univ. | Semi-supervised learning based on Dirichlet process mixture models Naonori Ueda, Takeshi Yamada, Shuhei Kuwata (NTT) DE2007-16 PRMU2007-42 |
[more] | DE2007-16 PRMU2007-42 pp.87-92 |
| PRMU, DE | 2007-06-29 15:45 |
Hokkaido | Hokkaido Univ. | Adaptive Parameter Estimation On Multiple-Target Tracking Problem Katsuhiko Ishiguro, Takeshi Yamada, Naonori Ueda (NTT) DE2007-19 PRMU2007-45 |
We address a parameter estimation problem for data association in multi-target tracking task. Many existing methods re... [more] |
DE2007-19 PRMU2007-45 pp.105-110 |
| AI | 2007-05-31 11:10 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | Collaborative Filtering using Purchase Sequences Tomoharu Iwata, Takeshi Yamada, Naonori Ueda (NTT) AI2007-3 |
We propose a collaborative filtering method that uses sequential information in purchase histories for recommendations. ... [more] | AI2007-3 pp.13-18 |
| AI | 2007-05-31 11:35 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | Personalized Recommendation by Identifying Innovator Noriaki Kawamae, Takeshi Yamada, Naonori Ueda (NTT) AI2007-4 |
(To be available after the conference date) [more] | AI2007-4 pp.19-24 |
| PRMU | 2006-12-15 10:00 |
Fukui | A Prediction Algorithm for the Collaborative Filtering Method based on Marginal Rating Distributions Shuhei Kuwata, Naonori Ueda (NTT) |
[more] | PRMU2006-172 pp.7-12 |
|
| PRMU | 2006-12-15 10:30 |
Fukui | Semi-supervised classification of heterogeneous data Akinori Fujino, Naonori Ueda, Kazumi Saito (NTT) |
[more] | PRMU2006-173 pp.13-18 |
|
| AI | 2006-05-18 10:45 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | A collaborative filtering method based on marginal rating distributions Shuhei Kuwata, Naonori Ueda (NTT) |
We propose a collaborative filtering method based on a probabilistic approach . In the proposed method, first empirical ... [more] | AI2006-3 pp.13-18 |
| AI | 2006-05-18 15:50 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | A study of hot topic extraction from document stream based on probabilistic models Manabu Kimura (NAIST), Kazumi Saito, Naonori Ueda (NTT) |
[more] | AI2006-10 pp.51-56 |
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