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Technical Committee on Information-Based Induction Sciences and Machine Learning (IBISML) (Searched in: 2024)
Search Results: Keywords 'from:2024-06-20 to:2024-06-20'
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IBISML, NC, IPSJ-BIO, IPSJ-MPS [detail] | 2024-06-21 14:20 |
Okinawa | OIST | Proposal of Node Fusion in MLP-Mixer Shogo Taneda, Yukari Yamauchi (NU)  NC2024-21 IBISML2024-21 |
Deep learning architectures are composed of layers that relate to given spatial positions and different spatial position... [more] | NC2024-21 IBISML2024-21 pp.136-139 |
| IBISML, NC, IPSJ-BIO, IPSJ-MPS [detail] | 2024-06-21 14:45 |
Okinawa | OIST | Self-Organizing Method for Word Embedding Hongyi Zhang, Yukari Yamauchi (NU) NC2024-22 IBISML2024-22 |
In natural language processing, word embedding is essential for vectorizing word features. Mikolov et al. proposed Word2... [more] | NC2024-22 IBISML2024-22 pp.140-145 |
| IBISML, NC, IPSJ-BIO, IPSJ-MPS [detail] | 2024-06-21 15:25 |
Okinawa | OIST | A Method to Investigate Joint Load Reduction by using Assistive Devices with Flexible Bodies Focusing on Nonlinear Elastic Force Investigated by fMBD Inverse Dynamic Analysis. Shintaro Kasai, Hiroaki Wagatsuma (Kyutech) NC2024-23 IBISML2024-23 |
Various exoskeleton-type orthotics have been developed in the aim of prevention of joint disorders by reducing the burde... [more] | NC2024-23 IBISML2024-23 pp.146-153 |
| IBISML, NC, IPSJ-BIO, IPSJ-MPS [detail] | 2024-06-21 15:50 |
Okinawa | OIST | An Ontology-Based Hierarchy to Analyze a Common Impression and Individual Differences in Natural Language Descriptions in Image Annotation Analyses Kosei Shibata, Wataru Oshiumi (Kyutech), Masayuki Fujiwara (Komatsu-U), Satoshi Nishida (NICT), Hiroaki Wagatsuma (Kyutech) NC2024-24 IBISML2024-24 |
In the cognitive science viewpoint, image annotation analyses are considerable as a tool to reproduce how humans feel fo... [more] | NC2024-24 IBISML2024-24 pp.154-160 |
| IBISML, NC, IPSJ-BIO, IPSJ-MPS [detail] | 2024-06-21 16:15 |
Okinawa | OIST | Ghost Octave Convolution Riku Kiuchi, Yuki Suzuki, Yukari Yamauchi (NU) NC2024-25 IBISML2024-25 |
Kai Han et al. proposed the Ghost module, an efficient method to create feature maps by dividing the conventional convol... [more] | NC2024-25 IBISML2024-25 pp.161-164 |
| IBISML, NC, IPSJ-BIO, IPSJ-MPS [detail] | 2024-06-21 16:40 |
Okinawa | OIST | Gradually Growing SparseNet Takumi Nakamura, Shogo Taneda, Yukari Yamauchi (NU) NC2024-26 IBISML2024-26 |
Gao Huang et al. proposed a Dense Convolutional Network (DenseNet) that takes the feature maps of all previous layers as... [more] | NC2024-26 IBISML2024-26 pp.165-168 |
| IBISML, NC, IPSJ-BIO, IPSJ-MPS [detail] | 2024-06-22 10:00 |
Okinawa | OIST | NC2024-27 IBISML2024-27 |
(To be available after the conference date) [more] | NC2024-27 IBISML2024-27 pp.169-173 |
| IBISML, NC, IPSJ-BIO, IPSJ-MPS [detail] | 2024-06-22 10:25 |
Okinawa | OIST | NC2024-28 IBISML2024-28 |
[more] | NC2024-28 IBISML2024-28 pp.174-177 |
| IBISML, NC, IPSJ-BIO, IPSJ-MPS [detail] | 2024-06-22 10:50 |
Okinawa | OIST | NC2024-29 IBISML2024-29 |
[more] | NC2024-29 IBISML2024-29 pp.178-181 |
| IBISML, NC, IPSJ-BIO, IPSJ-MPS [detail] | 2024-06-22 11:15 |
Okinawa | OIST | Oscillation-driven reservoir computing for long-term timing/chaotic time-series prediction Yuji Kawai (Osaka Univ.), Takashi Morita (Chubu Univ.), Park Jihoon (NICT/Osaka Univ.), Minoru Asada (IPUT/Osaka Univ./NICT/Chubu Univ.) NC2024-30 IBISML2024-30 |
Reservoir computing has been exploited for model-free prediction of various time series, including chaotic dynamical sys... [more] | NC2024-30 IBISML2024-30 pp.182-187 |
| IBISML, NC, IPSJ-BIO, IPSJ-MPS [detail] | 2024-06-22 11:40 |
Okinawa | OIST | Hierarchical reservoir computing model with circle topology for time series prediction and anomaly detection Wenkai Yu, Satoshi Moriya, Hideaki Yamamoto, Shigeo Sato (Tohoku Univ) NC2024-31 IBISML2024-31 |
Reservoir computing (RC), known for its high resource efficiency and ability to handle dynamic data, is gaining attentio... [more] | NC2024-31 IBISML2024-31 p.188 |
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