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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 86  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
IN, CCS
(Joint)
2022-08-04
10:00
Hokkaido Hokkaido University(Centennial Hall)
(Primary: On-site, Secondary: Online)
Investigation on Applying Data Augmentation to CycleGAN
Syuhei Kanzaki, Hidehiro Nakano (Tokyo City Univ.) CCS2022-26
In machine learning and deep learning, a huge amount of data is required for training. The image generation model GAN ex... [more] CCS2022-26
pp.1-5
CCS, NLP 2022-06-09
13:50
Osaka
(Primary: On-site, Secondary: Online)
Improvement of Learning Performance by Using a Symmetric Constraint Condition in PPO
Naoki Iwaya, Hidehiro Nakano (Tokyo City Univ.) NLP2022-3 CCS2022-3
Deep Reinforcement Learning (DRL) is an algorithm of learning the optimal action from the experiences. PPO KL Penalty, a... [more] NLP2022-3 CCS2022-3
pp.13-16
CCS, NLP 2022-06-09
14:15
Osaka
(Primary: On-site, Secondary: Online)
Improvement of Recognition Accuracy by Sequential Execution of Unsupervised Learning and Semi-supervised Learning
Hiroki Murakami, Hidehiro Nakano (Tokyo City Univ.) NLP2022-4 CCS2022-4
In this study, we propose a sequential learning method that improves recognition accuracy by alternately utilizing the k... [more] NLP2022-4 CCS2022-4
pp.17-22
CCS, NLP 2022-06-09
14:55
Osaka
(Primary: On-site, Secondary: Online)
Basic Performance of CNNs Using Dynamic Filters Based on Octave Convolution
Kiyotaka Matono, Hidehiro Nakano (Tokyo City Univ.) NLP2022-5 CCS2022-5
The methods of using dynamic filters for convolutional neural networks (CNNs) have attracted attentions. In recent years... [more] NLP2022-5 CCS2022-5
pp.23-26
CCS, NLP 2022-06-09
15:20
Osaka
(Primary: On-site, Secondary: Online)
Speeding-up by Reduction of Processing Paths in Octave Convolution
Akito Yoshikawa, Hidehiro Nakano (Tokyo City Univ.) NLP2022-6 CCS2022-6
Octave Convolution (OctConv), one of the convolutional neural network methods, can also improve accuracy while reducing ... [more] NLP2022-6 CCS2022-6
pp.27-30
CCS, NLP 2022-06-10
15:55
Osaka
(Primary: On-site, Secondary: Online)
Swarm intelligence algorithm based on spiking neural-oscillator networks, coupling interactions and solving performances
Tomoyuki Sasaki (SIT), Hidehiro Nakano (TCU) NLP2022-22 CCS2022-22
Optimizer based on spiking neural-oscillator networks (OSNN) are one of the deterministic swarm intelligence
algorithms... [more]
NLP2022-22 CCS2022-22
pp.111-116
NLP 2021-12-17
10:00
Oita J:COM Horuto Hall OITA Basic performances of a swarm intelligence algorithm based on spiking oscillator networks
Tomoyuki Sasaki (SIT), Hidehiro Nakano (TCU) NLP2021-43
Spiking oscillator networks are simply coupling systems of plural spiking oscillators, which generate various synchroniz... [more] NLP2021-43
pp.1-6
NLP 2021-12-17
10:50
Oita J:COM Horuto Hall OITA Reduction of Computation Cost for Self-Attention Networks Using Octave Convolution
Jun Kokubo, Hidehiro Nakano (Tokyo City Univ.) NLP2021-45
 [more] NLP2021-45
pp.13-17
NLP 2021-12-17
11:15
Oita J:COM Horuto Hall OITA Investigation on Distance Between Probability Distributions in Trust Region Policy Optimization
Kenta Sugaya, Hidehiro Nakano (Tokyo City Univ.) NLP2021-46
In this paper, we propose a method to change Kullback-Leibler Divergence to Jensen-Shannon Divergence that used in Trust... [more] NLP2021-46
pp.18-21
NLP 2021-12-18
15:15
Oita J:COM Horuto Hall OITA On Weight Filter Generation Using an Attention Module in a Super-Resolution Method
Keitaro Otani, Hidehiro Nakano (Tokyo City Univ.) NLP2021-66
In recent years, the development of computer technology has led to an increase in the number of systems that require lar... [more] NLP2021-66
pp.104-109
CCS 2021-03-29
15:40
Online Online A 3DCNN with Reduced Parameters Using Depthwise Separable Convolution
Koki Ito, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) CCS2020-27
Convolutional Neural Networks (CNNs) have been used in various fields such as image and speech. In recent years, CNNs ha... [more] CCS2020-27
pp.37-41
CCS 2021-03-29
16:05
Online Online IMAS-GAN: Unsupervised Domain Translation without Cycle Consistency
Masashi Okada, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) CCS2020-28
CycleGAN realizes the translation between domains without using pair data. However, the configuration of two GANs and th... [more] CCS2020-28
pp.42-47
CCS 2020-03-26
11:00
Tokyo Hosei Univ. Ichigaya Campus
(Cancelled but technical report was issued)
Generative Adversarial Networks Handling Multiple Distances between Probability Distributions
Shinya Hidai, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) CCS2019-39
Generative Adversarial Networks (GAN) are trained by alternately training two networks. Discriminator estimates the dist... [more] CCS2019-39
pp.21-24
NLP 2018-04-27
16:10
Kumamoto Kumaoto Univ. An ABC Algorithm with Improvement of Tracking Performance to Solutions in Dynamic Optimization Problems
Masato Omika, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) NLP2018-26
We propose an ABC algorithm to dynamic optimization problems in this article. The proposed method makes the following tw... [more] NLP2018-26
pp.127-131
NLP 2018-04-27
16:35
Kumamoto Kumaoto Univ. A Particle Swarm Optimizer Based on Periodically Swiched Particle Networks
Santana Sato, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) NLP2018-27
In this paper, we propose a method to periodically switch the couplings between particles in Particle Swarm Optimization... [more] NLP2018-27
pp.133-137
CCS 2018-03-26
10:00
Tokyo Tokyo Univ. of Sci. (Morito Memorial Hall) Suppression Method of Mode Collapse in Generative Adversarial Nets
Shinya Hidai, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) CCS2017-33
Generative Adversarial Nets (GAN) is constituted by two neural networks, Generator and Discrminator. Generator creates d... [more] CCS2017-33
pp.1-6
CCS 2017-08-11
11:00
Hokkaido Bibai Onsen Yu-rinkan A Flooding Scheme in Wireless Sensor Networks Using Integer-Valued Neuron Models
Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) CCS2017-16
In Wireless Sensor Networks, flooding is used in diffusing advertising messages, control messages, and so on.
If flood... [more]
CCS2017-16
pp.37-41
CCS 2017-08-11
12:30
Hokkaido Bibai Onsen Yu-rinkan A Study on Dynamic Grouping Schemes in Co-evolutional Particle Swarm Optimizers
Ryosuke Kikkawa, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) CCS2017-17
Particle Swarm Optimization (PSO) is one of optimization algorithms that imitate the behavior of organisms in a swarm.
... [more]
CCS2017-17
pp.43-46
NLP 2017-07-13
14:15
Okinawa Miyako Island Marine Terminal A Study on Two-Dimensional Cellular Automaton Rules for Encryption
Yuuki Hanaie, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) NLP2017-34
In this paper, we consider encryption using two-dimensional cellular automaton.As a round function for stirring the plai... [more] NLP2017-34
pp.35-39
NLP 2017-07-14
14:50
Okinawa Miyako Island Marine Terminal Multi-objective Particle Swarm Optimizer Networks with Tree Topology
Kyosuke Miyano, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) NLP2017-47
In this paper, we consider island-model multi-objective particle swarm optimization (IMOPSO) in which plural sub-swarms ... [more] NLP2017-47
pp.103-106
 Results 1 - 20 of 86  /  [Next]  
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