Systems and methods described herein relate to customized machine-learning-based model simplification for connected vehicles. One embodiment executes a first training procedure for a machine-learning-based teacher model and performs the following repeatedly until convergence occurs: (1) distributing, to connected vehicles, a set of teacher-model parameters from the teacher model; (2) receiving, from each connected vehicle, a set of student-model parameters for a student model trained through a second training procedure employing first knowledge distillation to mimic the teacher model, wherein the student model is less complex than the teacher model; and (3) executing a third training procedure including second knowledge distillation in which a combined model from the sets of student-model parameters acts as a quasi-teacher model to update the teacher model. After convergence, a vehicular application, instantiated in a connected vehicle, controls operation of the connected vehicle based, at least in part, on the student model in the connected vehicle.
SYSTEMS AND METHODS FOR CUSTOMIZED MACHINE-LEARNING-BASED MODEL SIMPLIFICATION FOR CONNECTED VEHICLES
15.08.2024
Patent
Elektronische Ressource
Englisch
IPC: | G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion / G05D SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES , Systeme zum Steuern oder Regeln nichtelektrischer veränderlicher Größen |
Topology simplification strategy for connected multi-agent systems
Kraftfahrwesen | 2011
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