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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 52  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
R 2023-03-10
14:50
Hiroshima
(Primary: On-site, Secondary: Online)
Model selection between logistic and Gompertz models
Daisuke Satoh (NTT) R2022-52
A discrete Gompertz model and model selection between the Gompertz and logistic models are proposed. The proposed method... [more] R2022-52
pp.25-30
MI 2023-03-06
09:44
Okinawa OKINAWA SEINENKAIKAN
(Primary: On-site, Secondary: Online)
Machine learning models using CT images and clinical variable to classify tumors in testicular cancer
Shota Nakagawa, Masanobu Gido (University of Tsukuba), Satoshi Nitta (University of Tsukuba Hospital), Takahiro Kojima (Aichi Cancer Center Hospital), Hideki Kakeya (University of Tsukuba) MI2022-75
This paper presents machine learning methods to classify tumors in testicular cancer. The model combines CT images and c... [more] MI2022-75
pp.8-13
NS, IN
(Joint)
2020-03-05
10:40
Okinawa Royal Hotel Okinawa Zanpa-Misaki
(Cancelled but technical report was issued)
A Media Access Control using Capture Effect based on Mathematical Model for Improving Throughput Fairness over Densely placed WLANs
Yoshiki Miura, Hiroyasu Obata, Chisa Takano, Kenji Ishida (Hiroshima City Univ.) IN2019-88
In an environment where multiple wireless LAN (WLAN) systems are densely placed, SACA (Semi-Active CW Adaptation) method... [more] IN2019-88
pp.73-78
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
R 2019-06-14
15:30
Tokyo Kikai-Shinko-Kaikan Bldg. Identification comparison of software fault-prone modules using nonlinear logistic regression models
Kazunari Yamanaka, Tadashi Dohi, Hiroyuki Okamura (Hiroshima U.) R2019-12
In this article, we compare several non-linear logistic regression models used in a fault-prone
identification problem... [more]
R2019-12
pp.19-24
NC, MBE
(Joint)
2018-12-15
15:30
Aichi Nagoya Institute of Technology Proposal of Analysis Accuracy Improvement Method by Logistic Regression in Single Nucleotide Polymorphism Analysis Using Next-Generation Sequencer
Ginji Azuma (Kindai Univ.), Atsushi Takahashi (NCVC), Naoki Ohboshi (Kindai Univ.) NC2018-37
Single nucleotide polymorphisms are known to be related to phenotypes, and analysis is actively performed. However, the ... [more] NC2018-37
pp.51-55
IBISML 2018-11-05
15:10
Hokkaido Hokkaido Citizens Activites Center (Kaderu 2.7) [Poster Presentation] Inference for Logitistic Regression Mixture Model with Local Variational Approximation and Study for Variational Free Energy
Fumito Nakamura, Ryosuke Konishi (Generic Solution), Yasushi Kiyoki (Keio) IBISML2018-48
A logistic regression mixture model (LRMM) is a mixed model of the Logistic regression model, and it is widely used in t... [more] IBISML2018-48
pp.29-36
CAS, NLP 2018-10-18
14:15
Miyagi Tohoku Univ. Estimation accuracy of causal relation on difference in network structures
Kazuya Sawada (TUS), Yutaka Shimada (Saitama Univ.), Tohru Ikeguchi (TUS) CAS2018-43 NLP2018-78
In this paper, we applied Convergent Cross Mapping to estimate causal relations between multiple timeseries. We used a c... [more] CAS2018-43 NLP2018-78
pp.33-38
KBSE, SS, IPSJ-SE [detail] 2018-07-18
10:30
Hokkaido   An analysis of the impact of temporal changes of developers' activities on the committer candidate prediction model
Daiki Yamasaki, Masao Ohira, Akinori Ihara, Yutaro Kashiwa, Tomoki Miyazaki (Wakayama Univ.) SS2018-4 KBSE2018-14
Many of large-scale open source projects have a serious problem in recruiting committers who have a privilege to commit ... [more] SS2018-4 KBSE2018-14
pp.19-24
SWIM 2018-05-19
14:15
Tokyo Kikai-Shinko-Kaikan Bldg. The Cyberspace Revolution -- Reconsidering Corporate Organizations --
Shoei Komatsu (APSOM) SWIM2018-2
Beginning in the era of the New Industrial Revolution, collaboration between companies, and the formation of business ec... [more] SWIM2018-2
pp.3-8
SIP, EA, SP, MI
(Joint) [detail]
2018-03-19
14:45
Okinawa   Optimization of Gaussian Kernel Parameters for Kernel Logistic Regression
Kosuke Fukumori, Tomoya Wada, Toshihisa Tanaka (TUAT) EA2017-135 SIP2017-144 SP2017-118
The kernel logistic regression is a nonlinear classification model that effectively uses kernel methods, which are one o... [more] EA2017-135 SIP2017-144 SP2017-118
pp.185-190
MBE, NC
(Joint)
2018-03-14
14:25
Tokyo Kikai-Shinko-Kaikan Bldg. Effect of Alzheimer's Disease on factors in waveform features of Pupil Light Reflex
Wioletta Nowak (Wroclaw Univ. of S&T), Minoru Nakayama (Tokyo Tech), Krecicki Tomasz (Wroclaw Medical Univ.), Andrzej Hachol (Wroclaw Univ. of S&T) MBE2017-107
Pupil light reflex (PLR) for 1 second chromatic stimuli was analysed to
develop a procedure of detecting Alzheimer's D... [more]
MBE2017-107
pp.131-136
SWIM 2018-02-23
15:15
Tokyo Kikai-Shinko-Kaikan Bldg. The Cyberspace Revolution -- Rethinking Business Engineering --
Shoei Komatsu (APSOM) SWIM2017-25
Due to the rapid spread of the Internet / IoT, the environment surrounding enterprises is rapidly changing. That is, for... [more] SWIM2017-25
pp.19-24
R 2017-10-20
14:25
Kumamoto   Logistic Curve's Parameter Fitting under Missing Data
Ryutaro Matsumura, Daisuke Satoh (NTT) R2017-45
The logistic difference equation can be solved by regression analysis to estimate parameters of logistic curve model wit... [more] R2017-45
pp.7-11
R 2016-10-21
13:30
Okinawa Okinawaken Seinenkaikan Analysis of the Ceiling by the Gompertz Curve Model with Data Described by the Logistic Curve Model
Daisuke Satoh, Ryutaro Matsumura (NTT) R2016-42
The Gompertz curve and logistic curve models are often used to forecast the ceiling. An accurate model selection method ... [more] R2016-42
pp.1-6
EA, ASJ-H 2016-08-09
13:30
Miyagi Tohoku Gakuin Univ., Tagajo Campus Improvement to an Objective Binaural Intelligibility Prediction Method
Kazuya Taira, Kazuhiro Kondo (Yamagata Univ.) EA2016-21
We attempted to improve the binaural intelligibility estimation method proposed in our previous paper. The number of dat... [more] EA2016-21
pp.7-12
NLC, TL 2016-06-04
16:50
Hokkaido Otaru University of Commerce Identification of Tweets that Mention Books -- Effects of Features, Data Size, and ML Algorithms --
Shuntaro Yada, Kyo Kageura (UTokyo) TL2016-7 NLC2016-7
We report performances of a classifier that identify Tweets that Mention Books (TMB) from tweets that contain the same s... [more] TL2016-7 NLC2016-7
pp.29-34
IA 2014-11-06
15:50
Overseas Thailand Isan Dhamma Character Recognition on Palm Leaves based on Logistic Model Tree
Preecha Khakham, Narumol Chumuang, Mahasak Ketcham (King Mongkut Univ. of Tech.) IA2014-55
This paper proposes a new approach for Isan Dhamma handwriting on palm leaves character recognition system based on Logi... [more] IA2014-55
pp.109-114
NLC 2014-06-15
09:25
Fukuoka Kyushu Institute of Technology Extraction of Determinants of Postoperative Length of Stay from Operation Records
Takanori Yamashita, Yoshifumi Wakata, Satoshi Hamai, Yasuharu Nakashima, Yukihide Iwamoto, Naoki Nakashima, Sachio Hirokawa (Kyushu Univ.) NLC2014-11
Secondary use of clinical text data are gaining much attention in improving the quality and the efficiency of medical tr... [more] NLC2014-11
pp.59-64
IBISML 2014-03-07
10:05
Nara Nara Women's University Online Prediction with Bradley-Terry Models and Logistic Models
Issei Matsumoto, Kohei Hatano, Eiji Takimoto (Kyushu Univ) IBISML2013-74
We consider an online density estimation problem under the Bradley-Terry model which determines the probability of the o... [more] IBISML2013-74
pp.55-62
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