Data-Specific Hyper-Parameter Design: A Paradigm Shift in Reservoir Computing

ArXi:2605.25221v1 Announce Type: cross Reservoir computing typically relies on large, randomly generated reservoirs, enabling simple, often linear readouts. Over the past two decades, most constructions have exploited the freedom to select the reservoir, constrained primarily by stability conditions based on state contraction or memory capacity. However, these designs are largely independent of the input data and learning objective, resulting in a trial-and-error methodology driven by randomness.