Search Results for author: Kazutaka Kanno

Found 6 papers, 0 papers with code

Attention-Enhanced Reservoir Computing

no code implementations27 Dec 2023 Felix Köster, Kazutaka Kanno, Jun Ohkubo, Atsushi Uchida

Photonic reservoir computing has been recently utilized in time series forecasting as the need for hardware implementations to accelerate these predictions has increased.

Temporal Sequences Time Series +1

Parallel photonic accelerator for decision making using optical spatiotemporal chaos

no code implementations12 Oct 2022 Kensei Morijiri, Kento Takehana, Takatomo Mihana, Kazutaka Kanno, Makoto Naruse, Atsushi Uchida

We solve a 512-armed bandit problem online, which is much larger than previous experiments by two orders of magnitude.

Decision Making

Controlling chaotic itinerancy in laser dynamics for reinforcement learning

no code implementations12 May 2022 Ryugo Iwami, Takatomo Mihana, Kazutaka Kanno, Satoshi Sunada, Makoto Naruse, Atsushi Uchida

In this paper, we propose a method for controlling the chaotic itinerancy in a multi-mode semiconductor laser to solve a machine learning task, known as the multi-armed bandit problem, which is fundamental to reinforcement learning.

BIG-bench Machine Learning reinforcement-learning +1

Adaptive model selection in photonic reservoir computing by reinforcement learning

no code implementations27 Apr 2020 Kazutaka Kanno, Makoto Naruse, Atsushi Uchida

Here, we propose a scheme of adaptive model selection in photonic reservoir computing using reinforcement learning.

Load Forecasting Model Selection +4

Generative adversarial network based on chaotic time series

no code implementations24 May 2019 Makoto Naruse, Takashi Matsubara, Nicolas Chauvet, Kazutaka Kanno, Tianyu Yang, Atsushi Uchida

Here we utilize chaotic time series generated experimentally by semiconductor lasers for the latent variables of GAN whereby the inherent nature of chaos can be reflected or transformed into the generated output data.

Generative Adversarial Network Time Series +1

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