Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
IE, MVE, CQ, IMQ (Joint) [detail] |
2024-03-15 10:30 |
Okinawa |
Okinawa Sangyo Shien Center (Primary: On-site, Secondary: Online) |
A Point Cloud Downsampling Method Considering Local Features for 3D Object Classification Ryota Sugimoto, Kenji Kanai, Shiori Maki, Jiro Katto (Waseda Univ.) IMQ2023-70 IE2023-125 MVE2023-99 |
In recent years, use of point cloud data has been considered for 3D spatial recognition. To reduce processing load cause... [more] |
IMQ2023-70 IE2023-125 MVE2023-99 pp.313-318 |
SIP, SP, EA, IPSJ-SLP [detail] |
2024-02-29 16:20 |
Okinawa |
(Primary: On-site, Secondary: Online) |
EA2023-77 SIP2023-124 SP2023-59 |
In this paper, we consider a dynamic sensor placement problem where sensors can move within a network over time. Sensor ... [more] |
EA2023-77 SIP2023-124 SP2023-59 pp.97-102 |
IN, IA (Joint) |
2023-12-22 15:00 |
Hiroshima |
Satellite Campus Hiroshima |
[Short Paper]
A Study on the Applicability of Graph Reduction to Evaluating the Robustness of Complex Networks Murakawa Yamato, Ryotaro Matsuo, Ryo Nakamura (Fukuoka Univ.) IA2023-53 |
Generally, the computational complexity of network simulation and machine learning based on graph structure such as GNN ... [more] |
IA2023-53 pp.48-52 |
PRMU |
2022-12-16 14:10 |
Toyama |
Toyama International Conference Center (Primary: On-site, Secondary: Online) |
Sampling Strategies in Data Pruning Ryota Higashi, Toshikazu Wada (Wakayama Univ.) PRMU2022-48 |
Data Pruning is a method of selecting the training data out of an entire training dataset so as to keep the accuracy aft... [more] |
PRMU2022-48 pp.85-90 |
CCS, NLP |
2022-06-10 10:55 |
Osaka |
(Primary: On-site, Secondary: Online) |
[Invited Talk]
Computation and learning based on dual stochasticity of the brain Jun-nosuke Teramae (Kyoto Univ.) NLP2022-16 CCS2022-16 |
Neurons and synapses in the brain are highly stochastic devices. Neurons responsible for signal propagation in the brain... [more] |
NLP2022-16 CCS2022-16 pp.78-83 |
LOIS, ICM |
2022-01-27 15:25 |
Online |
Online |
[Invited Talk]
Cyber Security with Human-in-the-Loop Machine Learning Masato Uchida (Waseda Univ.) ICM2021-38 LOIS2021-36 |
There have been many studies on methods to detect various malicious activities in cyberspace using machine learning mode... [more] |
ICM2021-38 LOIS2021-36 pp.31-33 |
NLP, MICT, MBE, NC (Joint) [detail] |
2022-01-23 10:55 |
Online |
Online |
Reward-oriented Environment Inference on Reinforcement Learning Kazuki Takahashi (Kogakuin Univ.), Tomoki Fukai (OIST), Yutaka Sakai (Tamagawa Univ.), Takashi Takekawa (Kogakuin Univ.) NC2021-42 |
Experiments on humans using the bandit problem have shown that dimensionality reduction of complex observations to a sta... [more] |
NC2021-42 pp.49-54 |
RISING (3rd) |
2021-11-16 09:30 |
Tokyo |
(Primary: On-site, Secondary: Online) |
On Attack Pattern Classification in IoT Networks for Network Intrusion Detection Systems Jesse Atuhurra, Takanori Hara (NAIST), Yuanyu Zhang (Xidian Univ.), Shoji Kasahara (NAIST) |
With the proliferation of IoT devices, IoT security problems arise. To protect heterogeneous connected devices in IoT ne... [more] |
|
LOIS |
2020-03-12 11:05 |
Okinawa |
Nobumoto Ohama Memorial Hall (Cancelled but technical report was issued) |
Distributed active learning achieving both of monitoring and efficient time-series data sampling for edge computing Osamu Saisho, Keiichiro Kashiwagi, Yui Saito, Tomoyuki Fujino (NTT) LOIS2019-73 |
For edge computing, there is still a great demand to upload only meaningful data to cloud,. However there is no practica... [more] |
LOIS2019-73 pp.97-101 |
WIT, SP |
2019-10-26 17:00 |
Kagoshima |
Daiichi Institute of Technology |
Neural Whispered Speech Detection with Imbalanced Learning Takanori Ashihara, Yusuke Shinohara, Hiroshi Sato, Takafumi Moriya, Kiyoaki Matsui, Yoshikazu Yamaguchi (NTT) SP2019-26 WIT2019-25 |
In this paper, we present a neural whispered-speech detection technique that offers utterance-level classification of wh... [more] |
SP2019-26 WIT2019-25 pp.51-56 |
IBISML |
2018-11-05 15:10 |
Hokkaido |
Hokkaido Citizens Activites Center (Kaderu 2.7) |
[Poster Presentation]
Proposal of Hyperparameter Optimization Framework Using a Non-Stationary Multi-Armed Bandit Algorithm Kenshi Abe, Masahiro Nomura (CA) IBISML2018-62 |
Hyperparameter optimization problem is an important problem that appears in areas such as machine learning. Hyperparamet... [more] |
IBISML2018-62 pp.135-142 |
EA, ASJ-H |
2017-07-20 15:00 |
Hokkaido |
Hokkaido Univ. |
[Invited Talk]
Revisiting VOCODER
-- Why I intentionally discard the original phase of the original speech? -- Hideki Kawahara (Wakayama Univ.) EA2017-4 |
VOCODER is a framework invented for narrow band communication about 80 years ago. It has been providing a productive bas... [more] |
EA2017-4 pp.21-26 |
PRMU, IBISML, IPSJ-CVIM [detail] |
2014-09-02 15:45 |
Ibaraki |
|
Sampling Learning Algorithm by Oracle Distribution Sho Sonoda, Noboru Murata (Waseda Univ.) PRMU2014-52 IBISML2014-33 |
A new sampling learning algorithm for neural networks is proposed. Based on the integral representation of neural networ... [more] |
PRMU2014-52 IBISML2014-33 pp.137-142 |
IBISML |
2012-11-08 15:00 |
Tokyo |
Bunkyo School Building, Tokyo Campus, Tsukuba Univ. |
Calculation Method for WAIC Using Sequential Importance Sampling Takushi Miki, Sumio Watanabe (Tokyo Tech) IBISML2012-70 |
The bayes generalization loss represents the distance of the predictive distribution and the true distribution.
It is u... [more] |
IBISML2012-70 pp.259-263 |
PRMU, NLC |
2012-06-29 17:00 |
Tokyo |
|
Bayesian Nonparametric Approach to Audio Event Detection Yasunori Ohishi (NTT), Daichi Mochihashi, Tomoko Matsui (ISM), Masahiro Nakano, Hirokazu Kameoka, Tomonori Izumitani, Kunio Kashino (NTT) NLC2012-9 PRMU2012-29 |
As the amount of available multimedia data increases, the technique to automatically extract the significant information... [more] |
NLC2012-9 PRMU2012-29 pp.37-42 |
CQ, CS (Joint) |
2011-04-21 10:25 |
Kagoshima |
Yakushima Environmental Culture Village Center |
Low-cost Traffic Classification Method for Large-scale ISP Takayuki Goto, Chikara Sasaki, Atsuo Tachibana, Shigehiro Ano (KDDI R&D Labs.) CQ2011-1 |
Quantifying the traffic volume of each protocol is useful for effective traffic engineering and network designing. A str... [more] |
CQ2011-1 pp.1-4 |
CS, SIP, CAS |
2011-03-03 17:10 |
Okinawa |
Ohhamanobumoto memorial hall (Ishigaki)( |
[Memorial Lecture]
Sampling Theory and Principle of Science Hidemitsu Ogawa (Tokyo Univ. School of Social Welfare) CAS2010-122 SIP2010-138 CS2010-92 |
The problem of sampling theorem is reformulated from the functional analytic point of view. As a result, it is shown tha... [more] |
CAS2010-122 SIP2010-138 CS2010-92 pp.119-126 |
IBISML |
2010-06-14 09:35 |
Tokyo |
Takeda Hall, Univ. Tokyo |
[Invited Talk]
Advances in Statistical Machine Learning
-- An Approach based on Probability Density Ratios -- Masashi Sugiyama (Tokyo Inst. of Tech.) IBISML2010-1 |
Recently, we developed a new ML framework that allows us to
systematically avoid density estimation. The key idea is t... [more] |
IBISML2010-1 p.1 |
NS, IN (Joint) |
2010-03-05 11:00 |
Miyazaki |
Miyazaki Phoenix Seagaia Resort (Miyazaki) |
Unsupervised Ensemble Anomaly Detection Method using Time-Periodical Packet Sampling Shuichi Nawata, Masato Uchida (Kyushu Inst. of Tech.), Yu Gu (NEC Labs America), Masato Tsuru, Yuji Oie (Kyushu Inst. of Tech.) IN2009-198 |
We propose an anomaly detection method that trains a baseline model describing the normal behavior of network traffic wi... [more] |
IN2009-198 pp.325-330 |
WIT, HIP, HCS |
2009-05-14 - 2009-05-15 |
Okinawa |
Okinawa Industry Support Center |
Manipulating Higher-order Impressions of a Class of 3D Objects Using the Morphable 3D Model
-- Measurement of Impressions by the SD Method and Psychological Evaluation of the Transformation -- Yoshinori Inaba (Hosei Univ.), Hanae Ishi (Miyagi National Tech.), Kochi Jumpei (Hosei Univ.), Jiro Gyoba (Tohoku Univ.), Shigeru Akamatsu (Hosei Univ.) |
This paper describes a method for achieving a novel design within a class of 3D objects that would create a preferred im... [more] |
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