公开(公告)号：US20250086522A1

公开(公告)日：2025-03-13

申请号：US18462914

申请日：2023-09-07

Applicant: Qualcomm Technologies, Inc.

Inventor： Lars VEEFKIND ,  Gabriele CESA

IPC: G06N20/20

Abstract: Certain aspects of the present disclosure provide techniques and apparatus for improved machine learning. A set of training data is accessed, and a transformation group comprising a plurality of group elements is determined. A set of unconstrained weights for a layer of the machine learning model is generated based on the set of training data. A set of parameter values for a likelihood function for the layer is generated based on the set of training data. A set of constrained weights is generated, based at least in part on the likelihood function and the set of unconstrained weights, such that the set of constrained weights is equivariant with respect to at least a subset of the plurality of group elements.