Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
RCC, ISEC, IT, WBS |
2024-03-13 - 2024-03-14 |
Osaka |
Osaka Univ. (Suita Campus) |
Efficient Replay Data Selection in Continual Federated Learning Model Yuto Kitano (Kobe Univ), Lihua Wang (NICT), Seiichi Ozawa (Kobe Univ) IT2023-96 ISEC2023-95 WBS2023-84 RCC2023-78 |
In this study, we propose a continual federated learning that can continuously learn distributed data generated daily by... [more] |
IT2023-96 ISEC2023-95 WBS2023-84 RCC2023-78 pp.135-141 |
EMM |
2024-01-16 15:25 |
Miyagi |
Tohoku Univ. (Primary: On-site, Secondary: Online) |
[Invited Talk]
Federated Learning with Enhanced Privacy Protection in AI Lihua Wang (NICT) EMM2023-83 |
Federated learning is a crucial methodology in artificial intelligence where multiple organizations collaborate to perfo... [more] |
EMM2023-83 p.19 |
ICM, NS, CQ, NV (Joint) |
2023-11-22 09:25 |
Ehime |
Ehime Prefecture Gender Equality Center (Primary: On-site, Secondary: Online) |
A Study on Transfer of Decision Tree for Operation of Future Managed Networks Takaaki Moriya, Takashi Mukai, Manabu Nishio, Ai Tsunoda, Ken Kanishima (NTT) ICM2023-26 |
When we build a new managed network, we need knowledge to solve various failures that will be occurred in the network. H... [more] |
ICM2023-26 pp.20-25 |
LOIS |
2023-03-13 16:35 |
Okinawa |
(Primary: On-site, Secondary: Online) |
Lifelog Data Analyses of SNS Users Based on Supervised Learning to Forecast the Number of Bookmarks of A Post Komei Arasawa, Shun Matsukawa, Nobuyuki Sugio, Naofumi Wada, Hiroki Matsuzaki (Hokkaido Univ. of Sci.) LOIS2022-56 |
It is an important issue to establish how to produce and transmit a post that triggers people's interest, in marketing a... [more] |
LOIS2022-56 pp.72-76 |
HWS, VLD |
2023-03-02 17:15 |
Okinawa |
(Primary: On-site, Secondary: Online) |
Communication-Efficient Federated Learning with Gradient Boosting Decision Trees Kotaro Shimamura, Shinya Takamaeda (UTokyo) VLD2022-99 HWS2022-70 |
Federated learning (FL) is a machine learning method in which clients learn cooperatively without disclosing private dat... [more] |
VLD2022-99 HWS2022-70 pp.137-142 |
IT |
2022-07-22 15:05 |
Okayama |
Okayama University of Science (Primary: On-site, Secondary: Online) |
Bayes Optimal Approximation Algorithm by Boosting-like Construction of Meta-Tree Sets in Classification on Decision Tree Model Ryota Maniwa, Naoki Ichijo, Koshi Shimada, Toshiyasu Matsushima (Waseda Univ.) IT2022-28 |
Decision trees are used for classification and regression such as predicting the objective variable corresponding to the... [more] |
IT2022-28 pp.67-72 |
KBSE, SWIM |
2022-05-20 14:00 |
Tokyo |
(Primary: On-site, Secondary: Online) |
Generating LTL formulas with Trace Examples Kota Komatsu, Hiroki Horita (Ibaraki Univ.) KBSE2022-1 SWIM2022-1 |
In declarative process mining, a user can verify a desired property in a business process by providing an LTL formula wi... [more] |
KBSE2022-1 SWIM2022-1 pp.1-6 |
SeMI |
2022-01-21 15:20 |
Nagano |
(Primary: On-site, Secondary: Online) |
[Short Paper]
Asynchronous Gradient-Boosted Decision Trees for Distributed Sensing Devices Yui Yamashita, Akihito Taya, Yoshito Tobe (Aoyama Gakuin Univ.) SeMI2021-64 |
Recently, wearable devices that install multiple sensors have been widely used. Although sensor data from these devices ... [more] |
SeMI2021-64 pp.45-47 |
SIP, IT, RCS |
2021-01-22 09:50 |
Online |
Online |
Selection of Interference Cancellation Technique Using Decision Trees for Uplink Non-orthogonal Multiple Access
-- Evaluation of Communication Success Rate in A Mobile Environment -- Noriaki Yamamoto (Meiji Univ.), Masafumi Moriyama, Kenichi Takizawa (NICT), Tetsushi Ikegami (Meiji Univ.) IT2020-85 SIP2020-63 RCS2020-176 |
As IoT(Internet of Things)develops, wireless access techniques that can effectively accommodate massive number of device... [more] |
IT2020-85 SIP2020-63 RCS2020-176 pp.119-124 |
HWS, VLD [detail] |
2020-03-06 10:30 |
Okinawa |
Okinawa Ken Seinen Kaikan (Cancelled but technical report was issued) |
A Consideration on Efficient Anomaly Detection Based on Isolation Forest Tsubasa Ikeda, Shinobu Nagayama, Masato Inagi, Shin'ichi Wakabayashi (HCU) VLD2019-125 HWS2019-98 |
Isolation Forest is a method to detect anomalies by ensemble learning of binary decision trees. It traverses each decisi... [more] |
VLD2019-125 HWS2019-98 pp.179-184 |
NS, ICM, CQ, NV (Joint) |
2019-11-21 11:20 |
Hyogo |
Rokkodai 2nd Campus, Kobe Univ. |
Experiment of DDoS Attack Detection with UTM Log Analysis Using Decision Tree Aoshi Fujioka, Hiroyuki Okazaki, Hikofumi Suzuki (Shinshu Univ.) NS2019-123 |
In recent years, AI technology such as machine learning has been developed and the number of application examples are in... [more] |
NS2019-123 pp.19-25 |
IT |
2019-07-25 14:50 |
Tokyo |
NATULUCK-Iidabashi-Higashiguchi Ekimaeten |
Bayes Optimal Classification on Decision Tree Model and Its Approximative Algorithm Using Ensemble Learning Nao Dobashi, Shota Saito, Toshiyasu Matsushima (Waseda Univ.) IT2019-17 |
In this paper we consider classification problem about discrete category $y$ regarding discrete variables $bm{x}$. Deci... [more] |
IT2019-17 pp.11-16 |
RCC, MICT |
2019-05-29 15:30 |
Tokyo |
TOKYO BIG SIGHT |
[Poster Presentation]
Development of Real-time Body Motion Identification System using Radio Channel Characteristics in Wireless BAN Yuki Ichikawa, Masahiro Mitta, Minseok Kim (Niigata Univ.) RCC2019-7 MICT2019-7 |
In this article, a real-time motion identification system is presented which has been developed based on the knowledge o... [more] |
RCC2019-7 MICT2019-7 pp.29-33 |
RCC, MICT |
2018-05-24 13:00 |
Tokyo |
Tokyo Big Sight |
[Poster Presentation]
Investigation of Feature Reduction for Body Motion Identification using Radio Channel Characteristics in Wireless BAN Yuki Ichikawa, Minseok Kim (Niigata Univ.) RCC2018-4 MICT2018-4 |
In this article, the reduction of the features used for human motion classification using decision tree machine learning... [more] |
RCC2018-4 MICT2018-4 pp.17-20 |
IBISML |
2018-03-05 13:50 |
Fukuoka |
Nishijin Plaza, Kyushu University |
Metric Learning for k-Nearest Neighbor Estimation using Multiple Distance Metrics Yokuto Seki, Noboru Murata (Waseda Univ.) IBISML2017-92 |
The relationship between unstructured datasets such as graphs can be measured by multiple distance metrics.
In this pap... [more] |
IBISML2017-92 pp.15-19 |
IBISML |
2017-11-09 13:00 |
Tokyo |
Univ. of Tokyo |
[Poster Presentation]
Empirical Bayesian Tree Masashi Sekino (SMN) IBISML2017-39 |
We propose a new decision tree learning algorithm ``Empirical Bayesian Tree (EBT)'', which models the outputs of a leaf ... [more] |
IBISML2017-39 pp.31-38 |
KBSE |
2017-09-19 12:35 |
Tokyo |
Doshisha Univ. Tokyo Branch Office |
A load balancing mechanism using shared state for tree processing in actor model Kouhei Sakurai (Kanazawa Univ.) KBSE2017-21 |
For machine learning and data mining, there are methods that deal with tree structure, and also their parallelization an... [more] |
KBSE2017-21 pp.1-6 |
PRMU, IBISML, IPSJ-CVIM [detail] |
2017-09-15 13:30 |
Tokyo |
|
Fast and General-Purpose Bayesian Optimization using Tree-Based Model with Gaussian Process Hiroo Iwanaga (Univ. of Tokyo/NTT DATA MSI), Yukio Ohsawa (Univ. of Tokyo) PRMU2017-48 IBISML2017-20 |
Bayesian optimization is an effective method for black-box optimization problems such as hyperparameter tuning of machin... [more] |
PRMU2017-48 IBISML2017-20 pp.67-74 |
ASN, MoNA, MICT (Joint) |
2017-01-20 14:15 |
Oita |
|
An Investigation of Body Motion Identification Method using Radio Channel Characteristics for BAN Context-Aware Communications Yuki Ichikawa, Minseok Kim (Niigata Univ.) MICT2016-74 |
In this article, human motion classification to realize context-aware BAN has been empirically investigated. We develope... [more] |
MICT2016-74 pp.53-56 |
AI |
2015-12-18 14:30 |
Okinawa |
|
Comparison of SVM and Decision Tree for Prediction of Postoperative Hospital Stay Yuusuke Adachi, Takanori Yamashita, Yosifumi Wakata (Kyushu Univ.), Hidehisa Soejima (Saiseikai Kumamoto Hospital), Naoki Nakashima, Sachio Hirokawa (Kyushu Univ.) AI2015-36 |
In the medical practice, vast medical data are accumulated every day with medical computerization now. Due to increasin... [more] |
AI2015-36 pp.59-64 |