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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| CAS, CS | 2023-03-02 15:40 |
Fukuoka | Kitakyushu International Conference Center (Primary: On-site, Secondary: Online) |
Sound Quality Improvement of Source Separation Signal by Binary Mask Taiga Saito, Kenji Suyama (Tokyo Denki Univ.)  CAS2022-122 CS2022-99 |
A two-microphone source separation method using multiple complex weighted sum circuits (WSCs) has been proposed. However... [more] | CAS2022-122 CS2022-99 pp.150-154 |
| VLD, DC, RECONF, ICD, IPSJ-SLDM (Joint) [detail] |
2021-12-01 09:45 |
Online | Online | Sparsity-Gradient-Based Pruning and the Vitis-AI Implementation for Compacting Deep Learning Models Hengyi Li, Xuebin Yue, Lin Meng (Ritsumeikan Univ.) VLD2021-22 ICD2021-32 DC2021-28 RECONF2021-30 |
The paper proposes a Sparsity-Gradient-Based layer-wise Pruning technique for compacting deep neural networks and accele... [more] | VLD2021-22 ICD2021-32 DC2021-28 RECONF2021-30 pp.31-36 |
| SIP | 2021-08-23 14:00 |
Online | Online | [Invited Talk]
Block-Sparse Estimation using Optimal Block Structure Hiroki Kuroda (Ritsumeikan Univ.) SIP2021-29 |
This talk presents a convex optimization based block-sparse estimation method which is effective even when concrete bloc... [more] | SIP2021-29 p.11 |
| RCC | 2021-01-22 13:30 |
Online | Online | Maximum Turn-off Control Based on Block-sparse Optimization and Its Feedback Control Takumi Iwata, Shun-ichi Azuma, Ryo Ariizumi, Toru Asai (Nagoya Univ.) RCC2020-34 |
In this paper, maximum turn-off control and its feedback control are considered. Maximum turn-off control is, in the cas... [more] | RCC2020-34 pp.1-3 |
| IT, SIP, RCS | 2020-01-24 13:25 |
Hiroshima | Hiroshima City Youth Center | Design of sparse filters using a neural network Taro Itani, Masayoshi Nakamoto (Hiroshima Univ.), Naoyuki Aikawa (Tokyo univ. of science) IT2019-75 SIP2019-88 RCS2019-305 |
A sparse filter is a digital filter that contains zero coefficients. By designing a sparse filter with a redundant filte... [more] | IT2019-75 SIP2019-88 RCS2019-305 pp.227-232 |
| NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] | 2019-06-17 13:00 |
Okinawa | Okinawa Institute of Science and Technology | Analysis and application of periodic orbits in dynamic binary neural networks Shota Anzai, Seitaro Koyama, Toshimichi Saito (HU) NC2019-1 |
This paper studies a simple dynamic binary neural network and its application. In the network, each neuron transforms ... [more] |
NC2019-1 p.1 |
| NC, MBE (Joint) |
2019-03-04 16:35 |
Tokyo | University of Electro Communications | Application of dynamic binary neural networks to central pattern generators Shota Anzai, shunsuke aoki, seitaro koyama, Toshimichi Saito (HU) NC2018-61 |
This paper studies basic dynamics of simple dynamic binary neural networks and their applications. The network is chara... [more] |
NC2018-61 pp.95-98 |
| KBSE, SC | 2018-11-09 11:30 |
Hyogo | Evaluation of the Effectiveness of Recommendation while Managing the Data Density of the Web Service-User Preference Rupasingha Arachchilage Hiruni Madhusha Rupasingha, Incheon Paik (UOA) KBSE2018-30 SC2018-25 |
Recommender systems become important in the research and commercial society, where many recommendation solutions have b... [more] |
KBSE2018-30 SC2018-25 pp.13-18 |
|
| SIP, EA, SP, MI (Joint) [detail] |
2018-03-20 09:00 |
Okinawa | [Poster Presentation]
Blind Source Separation Based on the Sparsity of Impulse Responses Ryota Oda, Daichi Kitahara, Akira Hirabayashi (Ritsumeikan Univ.) EA2017-164 SIP2017-173 SP2017-147 |
We propose a blind source separation (BSS) algorithm using a priori information of the mixing process based on the state... [more] | EA2017-164 SIP2017-173 SP2017-147 pp.341-346 |
|
| IBISML | 2016-11-17 14:00 |
Kyoto | Kyoto Univ. | [Poster Presentation]
MAP reconstruction of multi-coil MR image with tree-structured wavelet prior Yufu Kasahara, Masato Inoue (Waseda Univ), Kaori Togashi (Kyoto Univ) IBISML2016-84 |
The magnetic resonance (MR) imaging is important for medical evaluation. However, it suffers from a long observation tim... [more] | IBISML2016-84 pp.275-278 |
| NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] | 2016-07-05 16:25 |
Okinawa | Okinawa Institute of Science and Technology | Sparse Simultaneous Estimation of Phase Response Curves using Spike-Triggered Average Man Arakaki, Yasuhiko Igarashi (Univ. Tokyo), Toshiaki Omori (Kobe Univ.), Masato Okada (Univ. Tokyo/RIKEN) NC2016-7 |
Phase response curves (PRC) have been used extensively to estimate the response properties of neurons. A recent measure... [more] |
NC2016-7 pp.165-170 |
| RCS, IT, SIP | 2016-01-18 10:10 |
Osaka | Kwansei Gakuin Univ. Osaka Umeda Campus | Effectiveness of L1 Regularization for Sparse Impulse Response Estimation Using colored Noise Keito Kito, Ryo Tanaka, Takahiro Murakami (Meiji Univ.) IT2015-58 SIP2015-72 RCS2015-290 |
In this paper, we show an effectiveness of L1 regularization for a sparse impulse response estimation using a colored no... [more] | IT2015-58 SIP2015-72 RCS2015-290 pp.61-66 |
| PRMU, MI, IE, SIP | 2015-05-15 10:00 |
Mie | Kernel Estimation using Normalized Sparsity Measure and its Application to Video Restoration Yusuke Nojima, Xian-Hua Han, Yen-Wei Chen (Ritsumeikan Univ.) SIP2015-15 IE2015-15 PRMU2015-15 MI2015-15 |
Image and video restoration is to recover the high-quality (HQ) image/video from low-quality (LQ) one due to the possibl... [more] | SIP2015-15 IE2015-15 PRMU2015-15 MI2015-15 pp.77-82 |
|
| SIP, EA, SP | 2015-03-03 09:00 |
Okinawa | [Poster Presentation]
An efficient algorithm for convex clustering with l2 regularization for sparsification on probability simplex Suguru Yasutomi, Toshihisa Tanaka (Tokyo Univ. of Agriculture and Tech.) EA2014-96 SIP2014-137 SP2014-159 |
Clustering is one of the important problems in many fields such as engineering and statistics. Convex clustering is a cl... [more] | EA2014-96 SIP2014-137 SP2014-159 pp.127-132 |
|
| RCC | 2015-01-15 15:30 |
Aichi | Nagoya University | Extended L1 Optimal Control for Generating Discrete Control Signals Masaaki Nagahara, Kazunori Hayashi (Kyoto Univ.) RCC2014-71 |
In this presentation, we propose the extended $L^1$-optimal control, which is defined by a weighted sum of $L^1$ norms, ... [more] | RCC2014-71 pp.37-40 |
| IBISML | 2014-11-18 15:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Asymptotic Analysis of Variational Bayesian Latent Dirichlet Allocation Shinichi Nakajima (TU Berlin), Issei Sato, Masashi Sugiyama (Univ. of Tokyo), Kazuho Watanabe (Toyohashi Univ. of Tech.), Hiroko Kobayashi (Nikon) IBISML2014-64 |
Latent Dirichlet allocation (LDA) is a popular generative model of various objects such as texts and images, where an ... [more] |
IBISML2014-64 pp.219-226 |
| SR | 2014-10-31 15:25 |
Overseas | I2R, Singapore | [Requested Talk] Sparsity methods for networked control Masaaki Nagahara (Kyoto Univ.) SR2014-93 |
In this presentation, we introduce sparsity methods for networked control systems and show the effectiveness of sparse c... [more] | SR2014-93 pp.191-192 |
| SP, IPSJ-MUS | 2014-05-24 11:30 |
Tokyo | [研究紹介] A spectrogram-patch-input DNN model for detection and classification of acoustic events robust to speech overlapping scenarios Miquel Espi, Masakiyo Fujimoto, Yotaro Kubo, Tomohiro Nakatani (NTT) SP2014-17 |
This paper presents an acoustic event detection and classification method that learns features from spectrogram patches ... [more] | SP2014-17 pp.171-176 |
|
| SP | 2014-02-28 13:50 |
Tokushima | The University of Tokushima | [Invited Talk]
Non-negative matrix factorization and its applications to time series processing Hirokazu Kameoka (Univ. Tokyo/NTT) SP2013-116 |
In this paper, I will give a brief introduction to a data analysis technique called non-negative matrix factorization (N... [more] | SP2013-116 pp.31-36 |
| RCS, SIP | 2014-01-23 17:10 |
Fukuoka | Kyushu Univ. | [Invited Talk]
Compressed Sensing and its Applications in Communications Kazunori Hayashi (Kyoto Univ.) SIP2013-109 RCS2013-279 |
Linear simultaneous equations based on linear measurements have `a true solution', however, it is not possible to unique... [more] | SIP2013-109 RCS2013-279 pp.139-144 |
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