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Committee Date Time Place Paper Title / Authors Abstract Paper #
NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] 2019-06-18
Okinawa Okinawa Institute of Science and Technology Additive or Concatenating Skip-connections Overcome the Degradation Problem of the Classic Feedforward Neural Network
Yasutaka Furusho, Kazushi Ikeda (NAIST) NC2019-17 IBISML2019-15
The classic feedforward neural networks like the multilayer perceptron (MLP) degrades its empirical risk by training eve... [more] NC2019-17 IBISML2019-15
pp.75-80(NC), pp.97-102(IBISML)
NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] 2019-06-18
Okinawa Okinawa Institute of Science and Technology ResNet and Batch-normalization Improve Data Separation Ability
Yasutaka Furusho, Kazushi Ikeda (NAIST) NC2019-18 IBISML2019-16
The skip-connection and the batch-normalization (BN) in ResNet enable an extreme deep neural network to be trained with ... [more] NC2019-18 IBISML2019-16
pp.81-86(NC), pp.103-108(IBISML)
NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] 2019-06-18
Okinawa Okinawa Institute of Science and Technology Theoretical Analysis of the Fixup Initialization for Fast Convergence and High Generalization Ability
Yasutaka Furusho, Kazushi Ikeda (NAIST) NC2019-19 IBISML2019-17
The Fixup initialization is a new initialization method of ResNet for a fast convergence with a high learning rate of SG... [more] NC2019-19 IBISML2019-17
pp.87-92(NC), pp.109-114(IBISML)
IBISML 2019-03-06
Tokyo RIKEN AIP Effects of Batch-normalization on Fisher Information Matrix of ResNet
Yasutaka Furusho, Kazushi Ikeda (NAIST) IBISML2018-110
ResNet have intensively been studied and many techniques have been used for better performance.
Batch-normalization (BN... [more]
IBISML 2019-03-06
Tokyo RIKEN AIP Wider neural networks with ReLU activation generalize better
Yasutaka Furusho, Kazushi Ikeda (NAIST) IBISML2018-111
Model size determination is important in machine learning since a larger model leads to overfitting, that is, a small tr... [more] IBISML2018-111
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