Integration Gelernter Unterschiedlicher Verlustfunktionen in Tiefenlernmodellen

Details

Veröffentlichungs-Nr.

EP4583004

Aktenzeichen

EP24222362

Anmeldetag

20. Dezember 2024

Veröffentlichung

9. Juli 2025

Rechtsraum

EP

IPC

G06N3/045G06N3/084G06N3/09G06N5/02

Abstract

Systems and methods are disclosed herein for training a model with a learned loss function. In an example system, a first trained neural network is generated based on application of a first loss function, such as a predefined loss function. A set of values is extracted from one or more of the layers of the neural network model, such as the weights of one of the layers. A separate machine learning model is trained using the set of values and a set of labels (e.g., ground truth annotations for a set of data). The machine learning model outputs a symbolic equation based on the training. The symbolic equation is applied to the first trained neural network to generate a second trained neural network. In this manner, a learned loss function can be generated and used to train a neural network, resulting in improved performance of the neural network.

Anmelder

Firma

Microsoft Technology Licensing, LLC

Land

🇺🇸 USA

Fachgebiete