Online edition: ISSN 2432-6380
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IBISML2018-105
A connection between Kida's optimal signal approximation and the signal classification by maximizing margin
Takuro Kida (Tokyo Tech. Prof.EM), Yuichi Kida (Ohu Univ.)
pp. 1 - 8
IBISML2018-106
Expressive power of skip connection and network architecture
Jumpei Nagase, Tetsuya Ishiwata (Shibaura Inst. of Tech.)
pp. 9 - 15
IBISML2018-107
Efficient Exploration by Variational Information Maximizing Exploration on Reinforcement Learning
Kazuki Doi, Keigo Okawa (Gifu Univ.), Motoki Shiga (Gifu Univ./JST/RIKEN)
pp. 17 - 22
IBISML2018-108
Set transformer for coordinating outfits
Takuma Nakamura, Yuki Saito (ZOZO Research)
pp. 23 - 29
IBISML2018-109
A Study on Automatic Generation of False Data Injection Attack against Connected Car Service Based on Reinforcement Learning
Yuichiro Dan, Keita Hasegawa, Takafumi Harada, Tomoaki Washio, Yoshihito Oshima (NTT)
pp. 31 - 38
IBISML2018-110
Effects of Batch-normalization on Fisher Information Matrix of ResNet
Yasutaka Furusho, Kazushi Ikeda (NAIST)
pp. 39 - 44
IBISML2018-111
Wider neural networks with ReLU activation generalize better
Yasutaka Furusho, Kazushi Ikeda (NAIST)
pp. 45 - 50
IBISML2018-112
Shapelet-based Multiple-Instance Learning
Daiki Suehiro, Kohei Hatano (Kyushu Univ./RIKEN AIP), Eiji Takimoto (Kyushu Univ.), Shuji Yamamoto, Kenichi Bannai (Keio Univ./RIKEN AIP), Akiko Takeda (The Univ. of Tokyo/RIKEN AIP)
pp. 51 - 58
IBISML2018-113
Optimal Kernel for Mode Estimation via Kernel Density Estimation
Ryoya Yamasaki, Toshiyuki Tanaka (Kyoto Univ.)
pp. 59 - 64
IBISML2018-114
Magnetic Resonance Angiography Image Restoration by Super Resolution based on Deep Learning
Shizen Kitazaki, Masanori Kawakita, Yutaka Jitumatu (Kyushu Univ.), Shigehide Kuhara (Kyorin Univ.), Akio Hiwatashi, Jun'ichi Takeuchi (Kyushu Univ.)
pp. 65 - 72
IBISML2018-115
Acceleration of Boosting Discriminators Using Region Partition Learning and Its Application to Face Detectors
Takeshi Mori, Junichi Takeuchi, Masanori Kawakita (Kyushu Univ.)
pp. 73 - 80
IBISML2018-116
Evaluation of LGRF using RAVE in Go program
Tatsuya Shimizu, Yuta Hayama, Asuka Nakamura, Yoshitaka Maekawa (CIT)
pp. 81 - 85
Note: Each article is a technical report without peer review, and its polished version will be published elsewhere.