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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| 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 |
| CCS | 2017-06-29 13:30 |
Ibaraki | Ibaraki Univ. | A Complex-Valued Reinforcement Learning Method Using Complex-Valued Neural Networks Masaki Mochida, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) CCS2017-1 |
This paper proposes the method to approximate the action-value function in complex-valued reinforcement learning by usin... [more] | CCS2017-1 pp.1-5 |
| CCS | 2017-06-29 13:55 |
Ibaraki | Ibaraki Univ. | Consideration on Functions for Quantization in Quantized Neural Networks Takumi Kadokura, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) CCS2017-2 |
Quantized Neural Network (QNN) is a kind of neural networks in which its weights and activations are quantized. Since, Q... [more] | CCS2017-2 pp.7-10 |
| CQ | 2017-05-30 13:25 |
Miyazaki | Hotel Merieges (Miyazaki) | An optimization method for flooding in wireless networks Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) CQ2017-27 |
In Wireless Sensor Networks, flooding is used in diffusing advertising messages, control messages, and so on. If flood... [more] |
CQ2017-27 pp.75-78 |
| CQ (2nd) |
2016-10-06 14:20 |
Nagano | Naganoken Nokyo Building | [Poster Presentation]
A hierarchical routing algorithm for MANET based on multi-agent learning Yuki Hoshino, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) |
Mobile Ad-hoc Networks (MANETs) can construct impromptu networks by wireless mobile nodes without fixed infrastructure. ... [more] | |
| NLP | 2016-09-15 15:20 |
Hyogo | Konan Univ. | A particle swarm optimizer with two rotation modes Hidehiro Nakano, Tomoyuki Sasaki, Arata Miyauchi (Tokyo City Univ.) NLP2016-63 |
This article proposes a particle swarm optimizer (PSO) with two rotation modes. Each search particle in the proposed P... [more] |
NLP2016-63 pp.97-100 |
| CQ | 2016-08-30 11:15 |
Ibaraki | Tsukubasan | Performance evaluation of a routing algorithm in MANET based on multi-agent learning Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) CQ2016-63 |
This article evaluates the performances of a routing algorithm in MANET proposed in our previous works. In this method... [more] |
CQ2016-63 pp.83-86 |
| NLP | 2016-07-22 10:00 |
Hokkaido | Hokkaido Univ. Centennial Hall | An Artificial Bee Colony Algorithm Suited for Parallel Distributed Processing Yu Isono, Tomoyuki Sasaki, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) NLP2016-40 |
As approximate solutions in large-scale problems are obtained by evolutionary computation algorithms, many search indivi... [more] | NLP2016-40 pp.33-38 |
| NLP | 2016-05-27 10:15 |
Kochi | Kochi Univ. | Implementation of parallel particle swarm optimizers on PC cluster Hidehiro Nakano, Ryosuke Matsumoto, Tomoyuki Sasaki, Arata Miyauchi (Tokyo City Univ.) NLP2016-13 |
This paper proposes an implementation method of the particle swarm optimizer (PSO) to PC cluster. In PSO, many particles... [more] | NLP2016-13 pp.63-66 |
| NLP | 2016-03-25 10:00 |
Kyoto | Kyoto Sangyo Univ. | Implementation of a specific processor for particle swarm optimizer networks Atsushi Moriyasu, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) NLP2015-150 |
This paper attempts to implement a processor specialized for particle swarm optimizer networks on FPGA. In the particle ... [more] | NLP2015-150 pp.47-51 |
| NC, NLP (Joint) |
2016-01-29 09:55 |
Fukuoka | Kyushu Institute of Technology | Investigation on coupling parameters in deterministic PSO networks Tomoyuki Sasaki, Hidehiro Nakano, Arata Miyauchi, Akira Taguchi (Tokyo City Univ.) NLP2015-136 |
PSO networks (PSONs) which is networking PSO are one of the multi swarm techniques. In PSONs, since each sub-swarm group... [more] | NLP2015-136 pp.57-62 |
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