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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| CCS | 2019-11-15 10:20 |
Hyogo | Kobe Univ. | Deformation of Embedding Space for Image-Caption Retrieval Takashi Matsubara (Kobe Univ.)  CCS2019-31 |
[more] | CCS2019-31 pp.33-36 |
| CCS | 2019-11-15 10:45 |
Hyogo | Kobe Univ. | Deep Unsupervised Defect Segmentation Robust to Aleatoric Uncertainty Kazuki Sato, Kenta Hama, Takashi Matsubara, Kuniaki Uehara (Kobe Univ.) CCS2019-32 |
[more] | CCS2019-32 pp.37-40 |
| CCS | 2019-11-15 11:10 |
Hyogo | Kobe Univ. | Mental Disorder Diagnosis Based on fMRI Images by Deep Generative Model Using Attribute Koki Kusano, Tetsuo Tashiro, Takashi Matsubara, Kuniaki Uehara (Kobe Univ.) CCS2019-33 |
[more] | CCS2019-33 pp.41-44 |
| NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] | 2019-06-17 13:00 |
Okinawa | Okinawa Institute of Science and Technology | Reliability Assessment by Bayesian Deep Learning for Image-Caption Retrieval Task Kenta Hama, Takashi Matsubara, Kuniaki Uehara (Kobe Univ.) IBISML2019-1 |
Following the development of black-box machine learning algorithms, the practical demand of the re- liability assessment... [more] | IBISML2019-1 pp.1-8 |
| NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] | 2019-06-17 13:25 |
Okinawa | Okinawa Institute of Science and Technology | Adversarial Day-to-Night Conversion Supporting Object Detection for Autonomous Driving Kazuki Fujioka (Kobe Univ.), Takashi Machida (Toyota CRDL), Takashi Matsubara, Kuniaki Uehara (Kobe Univ.) IBISML2019-2 |
[more] | IBISML2019-2 pp.9-14 |
| NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] | 2019-06-17 13:50 |
Okinawa | Okinawa Institute of Science and Technology | Aleatoric Uncertainty-Aware Score for Deep Unsupervised Anomaly Segmentation Kazuki Sato, Kenta Hama, Takashi Matsubara, Kuniaki Uehara (Kobe Univ.) IBISML2019-3 |
[more] | IBISML2019-3 pp.15-20 |
| NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] | 2019-06-17 17:35 |
Okinawa | Okinawa Institute of Science and Technology | Mental Disorder Diagnosis Based on fMRI Images by Deep Privileged Attribute Model Koki Kusano, Tetsuo Tashiro, Takashi Matsubara, Kuniaki Uehara (Kobe Univ.) NC2019-12 |
Machine learning-based accurate diagnosis of mental disorders is expected to support finding their biomarkers and unders... [more] | NC2019-12 pp.45-50 |
| NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] | 2019-06-18 13:30 |
Okinawa | Okinawa Institute of Science and Technology | Hybrid Reinforcement and Imitation Learning for Human-Like Agents Rousslan Fernand Julien Dossa, Xinyu Lian (Kobe Uni), Hirokazu Nomoto (EQUOS RESEARCH), Takashi Matsubara, Kuniaki Uehara (Kobe Uni) NC2019-16 IBISML2019-14 |
Reinforcement learning methods achieve performance superior to humans in a wide range of complex tasks and uncertain env... [more] | NC2019-16 IBISML2019-14 pp.69-74(NC), pp.91-96(IBISML) |
| CCS | 2018-11-23 10:50 |
Hyogo | Kobe Univ. | A Human-Like Agent Based on a Hybrid of Reinforcement and Imitation Learning Xinyu Lian, Rousslan Fernand Julien Dossa (Kobe Univ.), Hirokazu Nomoto (EQUOS RESEARCH), Takashi Matsubara, Kuniaki Uehara (Kobe Univ.) CCS2018-41 |
Reinforcement learning (RL) makes it possible to build an efficient agent that handles tasks in complex and uncertain en... [more] | CCS2018-41 pp.45-50 |
| CCS | 2018-11-23 14:55 |
Hyogo | Kobe Univ. | Hypernetwork-based Implicit Posterior Estimation of CNN Kenya Ukai, Takashi Matsubara, Kuniaki Uehara (Kobe Univ.) CCS2018-45 |
Deep neural networks have a rich ability to learn complex representations and achieved remarkable results in various tas... [more] | CCS2018-45 pp.67-72 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2018-09-20 09:50 |
Fukuoka | Image-Caption Retrieval by Embedding to Gaussian Distribution Kenta Hama, Takashi Matsubara, Kuniaki Uehara (Kobe Univ.) PRMU2018-38 IBISML2018-15 |
To get distributed representations of words, one has typically embedded words to points. Recent studies successfully... [more] |
PRMU2018-38 IBISML2018-15 pp.17-20 |
|
| PRMU, IBISML, IPSJ-CVIM [detail] | 2018-09-20 09:40 |
Fukuoka | Image Patchwork Data Augmentation Ryo Takahashi, Takashi Matsubara, Kuniaki Uehara (Kobe Univ.) PRMU2018-43 IBISML2018-20 |
Deep convolutional neural networks (CNNs) have demonstrated remarkable results thanks to their numerous parameters. How... [more] |
PRMU2018-43 IBISML2018-20 pp.47-54 |
|
| IN, CCS (Joint) |
2018-08-02 13:50 |
Hokkaido | Kitayuzawa Mori-no-Soraniwa | Deep Generative Model Structured for Feature Extraction of fMRI Images Tetsuo Tashiro, Takashi Matsubara, Kuniaki Uehara (Kove Univ.) CCS2018-32 |
[more] | CCS2018-32 pp.29-32 |
| CCS | 2017-11-09 14:55 |
Osaka | Osaka Univ. | Investigation of Hebbian-Like Learning Algorithm Based on Feedback Alignment for Autoencoder Takashi Matsubara (Kobe Univ.) CCS2017-24 |
Multilayer perceptrons have been trained by the back-propagation (BP) algorithm. Recent studies on feedback alignment (F... [more] | CCS2017-24 pp.21-24 |
| CCS | 2016-11-04 11:15 |
Kyoto | Kyoto Sangyo Univ. (Musubiwaza Bldg.) | Unsupervised Learning with Spike-Timing Dependent Delay Learning Model Takashi Matsubara (Kobe Univ.) CCS2016-32 |
Precious timing of neuronal spikes is considered to play an important role in signal transmission and processing in cent... [more] | CCS2016-32 pp.13-16 |
| IN, ICTSSL, NWS (Joint) |
2016-10-20 11:25 |
Osaka | Osaka Uinv. | Reasoning daily activities of single life using environment sensing and indoor location Long Niu, Seiji Sakakibara, Seiki Tokunaga, Sachio Saiki, Takashi Matsubara, Masahide Nakamura, Kuniaki Uehara (Kobe Univ.) IN2016-49 |
[more] | IN2016-49 pp.7-8 |
| NLP | 2016-03-24 13:25 |
Kyoto | Kyoto Sangyo Univ. | Implementation of Boltzmann Machine by Asynchronous Network of Cellular Automaton-based Neurons Takashi Matsubara, Kuniaki Uehara (Kove Univ.) NLP2015-143 |
Artificial neural networks with stochastic state transitions, such as Deep Boltzmann Machine, have excelled other machin... [more] | NLP2015-143 pp.7-10 |
| NLP | 2014-12-03 16:50 |
Tokyo | Kyoto Univ. Tokyo Office | The STDP with subthreshold fluctuation agrees with various features of biological neural network Takashi Matsubara (Osaka Univ.), Hiroyuki Torikai (Kyoto Sangyo Univ.) NLP2014-107 |
[more] | NLP2014-107 pp.47-49 |
| NLP | 2014-01-22 12:50 |
Hokkaido | Niseko Park Hotel | Nonlinear Model of BOLD signal without detrending Takashi Matsubara (Osaka Univ.), Hiroyuki Torikai (Kyoto Sangyo Univ.), Tetuya Shimokawa (CiNet) NLP2013-152 |
This paper presents a nonlinear model of human brain response to visual stimuli according to BOLD signal scanned by fMRI... [more] | NLP2013-152 pp.123-126 |
| NLP | 2013-10-29 10:00 |
Kagawa | Sanport Hall Takamatsu | Modeling of BOLD signal in response to visual stimuli Takashi Matsubara (Osaka Univ.), Hiroyuki Torikai (Kyoto Sangyo Univ.), Tetuya Shimokawa, Kenji Leibnitz, Ferdinand Peper (CiNet) NLP2013-93 |
This paper presents a nonlinear model of human brain response to visual stimuli according to BOLD signal scanned by fMRI... [more] | NLP2013-93 pp.123-126 |
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