75 citations · 176 across the 19 of their papers we have counts for
19 papers
Solving multi-armed bandit problems using a chaotic microresonator comb
Jonathan Cuevas, Ryugo Iwami, Atsushi Uchida +2
The Multi-Armed Bandit (MAB) problem, foundational to reinforcement learning-based decision-making, addresses the challenge of maximizing rewards amidst multiple uncertain choices.…
Chaotic mode-competition dynamics in a multimode semiconductor laser with optical feedback and injection
Ryugo Iwami, Kazutaka Kanno, Atsushi Uchida
Photonic computing is attracting increasing interest to accelerate information processing in machine learning applications. The mode-competition dynamics of multimode semiconductor…
Parallel photonic accelerator for decision making using optical spatiotemporal chaos
Kensei Morijiri, Kento Takehana, Takatomo Mihana +3
Photonic accelerators have attracted increasing attention in artificial intelligence applications. The multi-armed bandit problem is a fundamental problem of decision making using…
Analysis of temporal structure of laser chaos by Allan variance
Naoki Asuke, Nicolas Chauvet, André Röhm +6
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.…
Parallel bandit architecture based on laser chaos for reinforcement learning
Takashi Urushibara, Nicolas Chauvet, Satoshi Kochi +5
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 m…
Controlling chaotic itinerancy in laser dynamics for reinforcement learning
Ryugo Iwami, Takatomo Mihana, Kazutaka Kanno +3
Photonic artificial intelligence has attracted considerable interest in accelerating machine learning; however, the unique optical properties have not been fully utilized for achie…