Zobrazeno 1 - 10
of 555
pro vyhledávání: '"UCHIDA, Atsushi"'
Photonic reservoir computing has been successfully utilized in time-series prediction as the need for hardware implementations has increased. Prediction of chaotic time series remains a significant challenge, an area where the conventional reservoir
Externí odkaz:
http://arxiv.org/abs/2312.16503
Photonic computing has been widely used to accelerate the computational performance in machine learning. Photonic decision-making is a promising approach that uses photonic computing technologies to solve the multi-armed bandit problem based on reinf
Externí odkaz:
http://arxiv.org/abs/2312.16798
The Multi-Armed Bandit (MAB) problem, foundational to reinforcement learning-based decision-making, addresses the challenge of maximizing rewards amidst multiple uncertain choices. While algorithmic solutions are effective, their computational effici
Externí odkaz:
http://arxiv.org/abs/2308.10590
Publikováno v:
Commun Phys 6, 250 (2023)
High-speed machine vision is increasing its importance in both scientific and technological applications. Neuro-inspired photonic computing is a promising approach to speed-up machine vision processing with ultralow latency. However, the processing r
Externí odkaz:
http://arxiv.org/abs/2302.07875
Photonic computing is attracting increasing interest to accelerate information processing in machine learning applications. The mode-competition dynamics of multimode semiconductor lasers is useful for solving the multi-armed bandit problem in reinfo
Externí odkaz:
http://arxiv.org/abs/2211.08185
Autor:
Morijiri, Kensei, Takehana, Kento, Mihana, Takatomo, Kanno, Kazutaka, Naruse, Makoto, Uchida, Atsushi
Photonic accelerators have attracted increasing attention in artificial intelligence applications. The multi-armed bandit problem is a fundamental problem of decision making using reinforcement learning. However, the scalability of photonic decision
Externí odkaz:
http://arxiv.org/abs/2210.06976
Autor:
Asuke, Naoki, Chauvet, Nicolas, Röhm, André, Kanno, Kazutaka, Uchida, Atsushi, Niiyama, Tomoaki, Sunada, Satoshi, Horisaki, Ryoichi, Naruse, Makoto
Allan variance has been widely utilized in evaluating the stability of the time series generated by atomic clocks and lasers, in time regimes ranging from short to extremely long. This multi-scale examination capability of the Allan variance may also
Externí odkaz:
http://arxiv.org/abs/2208.02961
Autor:
Urushibara, Takashi, Chauvet, Nicolas, Kochi, Satoshi, Sunada, Satoshi, Kanno, Kazutaka, Uchida, Atsushi, Horisaki, Ryoichi, Naruse, Makoto
Accelerating artificial intelligence by photonics is an active field of study aiming to exploit the unique properties of photons. Reinforcement learning is an important branch of machine learning, and photonic decision-making principles have been dem
Externí odkaz:
http://arxiv.org/abs/2205.09543
Autor:
Iwami, Ryugo, Mihana, Takatomo, Kanno, Kazutaka, Sunada, Satoshi, Naruse, Makoto, Uchida, Atsushi
Photonic artificial intelligence has attracted considerable interest in accelerating machine learning; however, the unique optical properties have not been fully utilized for achieving higher-order functionalities. Chaotic itinerancy, with its sponta
Externí odkaz:
http://arxiv.org/abs/2205.05987