公开(公告)号：US20240256860A1

公开(公告)日：2024-08-01

申请号：US18424024

申请日：2024-01-26

Applicant: Mobileye Vision Technologies Ltd.

Inventor： Shai Shalev-Shwartz ,  Eran Malach ,  Gal Kaplun ,  Andrey Gurevich ,  Mazor David ,  Tal Swisa

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: Systems and methods generate an extended trained model. In one implementation, a method includes obtaining a preexisting trained model, the preexisting trained model including a plurality of preexisting weights, wherein each of the plurality of preexisting weights is associated with a preexisting value; identifying a subset of the plurality of preexisting weights; generating a plurality of extended weights based on a training process using duplicates of the subset of the plurality of preexisting weights; and generating the extended trained model, wherein the extended trained model includes the plurality of preexisting weights and the plurality of extended weights.

公开(公告)号：US20240394598A1

公开(公告)日：2024-11-28

申请号：US18666306

申请日：2024-05-16

Applicant: MobilEye Vision Technologies Ltd.

Inventor： Etay Zvi Livne ,  Gal Kaplun ,  Eran Malach ,  Shai Shalev-Shwartz

IPC: G06N20/00

Abstract: For example, a Machine-Learning (ML) model training system may be configured to shuffle a plurality of input examples in plurality of input blocks to provide a plurality of first-shuffled examples in a plurality of shuffled blocks; and to provide the plurality of first-shuffled examples in the plurality of shuffled blocks as an input to a model training procedure to train an ML model. For example, the model training procedure may include a plurality of epoch iterations applied to a plurality of block groups. For example, an epoch iteration may include determining a block group for the epoch iteration by randomly selecting a group of shuffled blocks from the plurality of shuffled blocks; shuffling first-shuffled examples in the block group to provide a plurality of second-shuffled examples; and updating the ML model according to a plurality of update iterations applied to the plurality of second-shuffled examples.