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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MVE, VRSJ-SIG-MR, IPSJ-EC, HI-SIG-DeMO, VRSJ-SIG-CS | 2023-10-27 11:40 |
Hokkaido | Online Structured Job Interview Assessment Using Multimodal Transformer and Prompt Learning Shengzhou Yi (UTokyo), Toshiaki Yamasaki (taleasse), Toshihiko Yamasaki (UTokyo)  MVE2023-28 |
Online interviews have gained significant traction in recruitment processes due to their enhanced efficiency. Among vari... [more] | MVE2023-28 pp.34-39 |
|
| SS | 2023-03-14 11:00 |
Okinawa | (Primary: On-site, Secondary: Online) |
A Technique for Detecting Missing Statements in Requirement Specifications Using Data Dependencies Shinnosuke Hirooka (Nanzan univ.), Motoshi Saeki (Nanzan Univ.) SS2022-47 |
Requirements specifications are often written in natural language and often defects such as ambiguous， contradictory, or... [more] | SS2022-47 pp.1-6 |
| IN | 2022-01-18 11:35 |
Online | Online | Evaluation on Prediction Method for Missing Probability of Sensor Value based on Hierarchical Structure of Missing Value Norifumi Hirata, Osamu Maeshima, Kiyohito Yoshihara (KDDI Research) IN2021-25 |
Collecting sensor data via networks is important for IoT (Internet of Things) services.However, sensors sometimes have m... [more] | IN2021-25 pp.7-12 |
| CS, IN, NS, NV (Joint) |
2020-09-11 13:45 |
Online | Online | Proposal and Evaluation on Prediction Method for Electricity Using Probability of Missing Sensor Value Norifumi Hirata, Osamu Maeshima, Kiyohito Yoshihara (KDDI Research) IN2020-27 |
VPP (Virtual Power Plant) is known as a system for electric power demand-supply adjustment. VPP is realized by controls... [more] |
IN2020-27 pp.31-36 |
| R | 2019-07-26 15:55 |
Iwate | Ichinoseki Cultural Center | More precise fitting of logistic curve model with missing data Daisuke Satoh, Ryutaro Matsumura (NTT) R2019-18 |
A parameter estimating method based on a logistic curve model with missing data is proposed. Since the model is describe... [more] | R2019-18 pp.25-29 |
| CPSY, DC, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC [detail] | 2017-03-10 08:50 |
Okinawa | Kumejima Island | Interpolation Method Using Cyclic Characteristics of Time-series Power Consumption Data Takahiro Hosoe, Tomoya Imanishi, Hiroaki Nishi (Keio Univ.) CPSY2016-142 DC2016-88 |
Smart meter and Internet of Things (IoT) has engendered the increase in the amount of data and the advance in data analy... [more] | CPSY2016-142 DC2016-88 pp.279-284 |
| IBISML | 2017-03-07 13:00 |
Tokyo | Tokyo Institute of Technology | Classification of In-week and -day Patterns of Ambulatory Activity Using a Hierarchical Topic Model and Interpolation of Step Counts in Missing Days Shunichi Nomura (Tokyo Tech.), Michiko Watanabe, Yuko Oguma (Keio Univ.) IBISML2016-109 |
In this study, we extract in-week and -day patterns of ambulatory activity based on hourly recorded step counts. A hiera... [more] | IBISML2016-109 pp.71-76 |
| DE | 2016-09-14 11:00 |
Kanagawa | Keio Univ. (Hiyoshi Campus) | A study of handling Missing Values Collaborative Filtering using Deep Learning Kohei Tanaka, Aki Kobayashi (Kogakuin Univ.) DE2016-20 |
Collaborative filtering (CF) processing using Deep Neural Network (dNN) for recommender systems have been developed. T... [more] |
DE2016-20 pp.49-52 |
| NC | 2015-01-29 16:05 |
Fukuoka | Kyushu Institute of Technology | Robustness of Tensor SOM for Missing Data Yasuhiro Wakita, Toru Iwasaki, Tetsuo Furukawa (Kyutech) NC2014-61 |
Tensor SOM is an extension of the self-organizing map (SOM), which enables us to visualize simultaneous visualization of... [more] | NC2014-61 pp.21-26 |
| IBISML | 2014-03-06 14:55 |
Nara | Nara Women's University | Consideration of Correlation between Users' Evaluating Values and Their Dropouts in Missing Value Prediction Kenta Nishimura, Toshiyuki Tanaka (Kyoto Univ.) IBISML2013-71 |
In user-item relational data, there are sometimes correlations between values and their dropouts. Existing methods under... [more] | IBISML2013-71 pp.31-38 |
| ASN, MoNA (Joint) |
2014-01-24 11:40 |
Ehime | Hotel Okudogo (Matsuyama) | Approach for Quantification Realization of Interpersonal Emotions Miyuki Imada (NTT), Kei Hirose (Osaka Univ.), Manabu Yoshida (NTT DOCOMO), Masato Matsuo (NTT) ASN2013-144 |
We have made a challenge for quantification realization of interpersonal emotion, which is emotion strength for another ... [more] | ASN2013-144 pp.153-158 |
| SR, AN, USN, RCS (Joint) |
2012-10-19 15:55 |
Fukuoka | Fukuoka univ. | Variable Selection Method in Multiple Regression with Incomplete Sensor Data Hisashi Kurasawa, Hiroshi Sato, Atsushi Yamamoto, Hitoshi Kawasaki, Motonori Nakamura, Hajime Matsumura (NTT) USN2012-54 |
Participatory sensing brings incomplete sensor data due to the spatio-temporal uncertainty of the observation. We have t... [more] | USN2012-54 pp.149-154 |
| NC | 2012-10-04 16:40 |
Fukuoka | Kyushu Institute of Technology (Wakamatsu Campus) | Tensor Decomposition using Self-Organizing Map and Missing Data Estimation Toru Iwasaki, Tetsuo Furukawa (KIT) NC2012-46 |
The aim of this work is to develop a nonlinear tensor decomposition algorithm based on the self-organizing map (SOM), ... [more] |
NC2012-46 pp.55-60 |
| IN, RCS (Joint) |
2012-05-17 15:15 |
Tokyo | Kuramae-Kaikan, Tokyo Institute of Technology | A Missing Data Recovery Scheme Using Low-Rank Approximation in Wireless Sensor Networks Takahiro Matsuda (Osaka Univ.) IN2012-15 |
In wireless network, error-prone wireless links may cause loss of transmitted data. In this article, we propose a missin... [more] | IN2012-15 pp.19-24 |
| AI | 2011-11-21 13:00 |
Fukuoka | An Imputation of context data by using Random Forest Tsunenori Ishioka (NCUEE) AI2011-21 |
When considering contextware services, we set the response variable to the services to provide, and explanatory variable... [more] | AI2011-21 pp.25-30 |
|
| NC | 2010-01-19 14:20 |
Hokkaido | Hyakunen-Kinen in Hokkaido University | An Extension of Matrix Factorization to Mixture Model and an Application to Prediction of Movie Ratings Masayoshi Nakamura, Takashi Takenouchi, Kazushi Ikeda (NAIST) NC2009-86 |
Recommendation systems suggest items to an user, based on existing history of evaluation for itemsby the users. In many ... [more] | NC2009-86 pp.89-93 |
| PRMU | 2009-11-27 09:30 |
Ishikawa | Ishikawa Industrial Promotion Center | Matrix factorization approaches to Projective reconstruction (2)
-- Performance comparison: CBC method vs. factorization based on the subspace constraints -- Eijiro Shibusawa, Wataru Mitsuhashi (Univ. of Electro-Comm.) PRMU2009-113 |
In this paper we perform a comparative study of two projective reconstruction algorithms: the CBC method proposed in... [more] |
PRMU2009-113 pp.139-144 |
| NC | 2009-01-19 11:45 |
Hokkaido | Hokkaido Univ. | A probabilistic model of maximum margin matrix factorization with ARD prior Masahiro Furuya (Nara Inst. of Scie and Tech), Shigeyuki Oba (Kyoto Univ.), Shin Ishii (Nara Inst.of Scie and Tech/Kyoto Univ.) NC2008-85 |
Various methods for missing value estimation of matrix data have been proposed based on low-rank approximation of matrix... [more] | NC2008-85 pp.19-24 |
| PRMU | 2008-10-23 11:30 |
Tokushima | Tokushima Univ. | Matrix factorization approaches to Projective reconstruction
-- CBC and SBC method for gluing partial reconstructions -- Eijiro Shibusawa, Wataru Mitsuhashi (Univ. Electro-Communications) PRMU2008-90 |
This paper presents factorization based approach to estimate projective structure of a static scene from the image corre... [more] | PRMU2008-90 pp.13-18 |
| ITS, IPSJ-ITS, IEE-ITS | 2007-09-18 14:00 |
Tokyo | Institute of Industrial Science, University of Tokyo | Dynamic prediction of traffic congestion using feature space trajectory Masatoshi Kumagai, Tomoaki Hiruta, Kouichirou Tanikoshi, Takayoshi Yokota (Hitachi Ltd.) |
This paper discusses a dynamic prediction method of traffic congestion using sparse floating car data (FCD.) Floating ca... [more] | ITS2007-17 pp.1-6 |
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