From the 1 of 8 linked papers with an AI index.
8 papers
Approximate reservoir computing with a semiconductor laser for reducing energy consumption
Tatsuki Ito, Kazutaka Kanno, Satoshi Kawakami +1
Photonic reservoir computing is a promising physical machine-learning technique for predicting time-series data. The quantization of the response signal from the reservoir is requi…
Photonic reservoir computing with complex networks
Sion Park, Kohei Watabe, Satoshi Sunada +2
Photonic reservoir computing has attracted increasing attention as a fast and low-cost approach for time-series prediction. Photonic reservoir computing utilizes the high speed, br…
Autocorrelation effects in a stochastic-process model for solving two-armed bandit problems
Tomoki Yamagami, Mikio Hasegawa, Takatomo Mihana +2
The paper studies how autocorrelation in photonic chaotic signals influences the performance of a stochastic-process model for solving two-armed bandit problems, showing that negat…
Quantum spatial best-arm identification via quantum walks
Tomoki Yamagami, Etsuo Segawa, Takatomo Mihana +3
Quantum reinforcement learning has emerged as a framework combining quantum computation with sequential decision-making, and applications to the multi-armed bandit (MAB) problem ha…
Adaptive Sensing of Continuous Physical Systems for Machine Learning
Felix Köster, Atsushi Uchida
Physical dynamical systems can be viewed as natural information processors: their systems preserve, transform, and disperse input information. This perspective motivates learning n…
Photonic decision making using optical frequency difference detection in mutually-coupled semiconductor lasers
Hidetoshi Taira, Takatomo Mihana, Shun Kotoku +4
As electronic computing approaches its performance limits, photonic accelerators have emerged as promising alternatives. Photonic accelerators exploiting semiconductor-laser synchr…