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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IPSJ-SLDM, RECONF, VLD, CPSY, IPSJ-ARC [detail] | 2020-01-24 11:25 |
Kanagawa | Raiosha, Hiyoshi Campus, Keio University | Implementation of high speed rainbow table generation using Keccak hashing algorithm on CUDA Nguyen Dat Thuong, Keisuke Iwai, Takashi Matsubara, Takakazu Kurokawa (NDA)  VLD2019-84 CPSY2019-82 RECONF2019-74 |
This paper proposes the implementation of high speed rainbow table generation using Keccak hashing algorithm with the in... [more] | VLD2019-84 CPSY2019-82 RECONF2019-74 pp.181-186 |
| HWS (2nd) |
2019-12-06 16:00 |
Tokyo | Asakusabashi Hulic Conference | [Poster Presentation]
Correlation power analysis and its countermeasure for lightweight ciphers LED and SKINNY implemented in SAKURA-X FPGA Hayato Tanaka, Keisuke Iwai, Takashi Matsubara, Takakazu Kurokawa (NDA) |
[more] | |
| CCS | 2019-11-14 13:25 |
Hyogo | Kobe Univ. | Calibration of Confidence in Deep Learning under Dataset Shift Kazuki Yoshida, Takashi Matsubara, Kuniaki Uehara (Kobe Univ.) CCS2019-25 |
Calibration of confidence is important when you want to obtain not only the prediction class of unknown data but also th... [more] | CCS2019-25 pp.5-8 |
| 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 |
| EA, ASJ-H, ASJ-AA | 2018-07-24 13:00 |
Hokkaido | Hokkaido Univ. | [Poster Presentation]
Denoising Method for Underwater Acoustic Signals by Using Hough Transform Yoshihiro Taira, Takashi Matsubara, Keisuke Iwai, Takakazu Kurokawa (NDA) EA2018-11 |
Underwater acoustic signals are used in various fields such as marine environmental measurement, exploration of sea bott... [more] | EA2018-11 pp.59-64 |
| 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 |
| AP | 2017-08-24 10:00 |
Hokkaido | National Institute of Technology, Hakodate College | DOA Estimation for Coprime Arrays Without Knowledge of Source Number Anh-Tuan Nguyen, Takashi Matsubara, Takakazu Kurokawa (NDA) AP2017-69 |
Pal et al. use a coprime array to extend it to a larger virtual ULA, and after spatial smoothing technique is implemente... [more] | AP2017-69 pp.7-12 |
| AP | 2016-12-08 13:25 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | High Performance DOA Estimation Method for Copime Arrays and Nested Arrays Anh-Tuan Nguyen, Takashi Matsubara, Takakazu Kurokawa (NDA) AP2016-126 |
In this paper, we consider a coprime array or nested array. Pal et al. have proposed a method to extend these arrays to ... [more] | AP2016-126 pp.17-22 |
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