公开(公告)号：US12165082B1

公开(公告)日：2024-12-10

申请号：US16915610

申请日：2020-06-29

Applicant: Amazon Technologies, Inc.

Inventor： Giovanni Zappella ,  Valerio Perrone ,  Iaroslav Shcherbatyi ,  Rodolphe Jenatton ,  Cedric Philippe Archambeau ,  Matthias Seeger

IPC: G06N7/01 ,  G06N3/08 ,  G06N20/00

Abstract: Hyperparameters for tuning a machine learning system may be optimized using Bayesian optimization with constraints. The hyperparameter optimization may be performed for a received training set and received constraints. Respective probabilistic models for the machine learning system and constraint functions may be initialized, then hyperparameter optimization may include iteratively identifying respective values for hyperparameters using analysis of the respective models performed using an acquisition function implementing entropy search on the respective models, training the machine learning system using the identified values to determine measures of accuracy and constraint metrics, and updating the respective models using the determined measures.

公开(公告)号：US20250013899A1

公开(公告)日：2025-01-09

申请号：US18888047

申请日：2024-09-17

Applicant: Amazon Technologies, Inc.

Inventor： Giovanni Zappella ,  Valerio Perrone ,  Iaroslav Shcherbatyi ,  Rodolphe Jenatton ,  Cedric Philippe Archambeau ,  Matthias Seeger

IPC: G06N7/01 ,  G06N3/08 ,  G06N20/00

Abstract: Hyperparameters for tuning a machine learning system may be optimized using Bayesian optimization with constraints. The hyperparameter optimization may be performed for a received training set and received constraints. Respective probabilistic models for the machine learning system and constraint functions may be initialized, then hyperparameter optimization may include iteratively identifying respective values for hyperparameters using analysis of the respective models performed using an acquisition function implementing entropy search on the respective models, training the machine learning system using the identified values to determine measures of accuracy and constraint metrics, and updating the respective models using the determined measures.