Invention Grant
- Patent Title: Resource constrained neural network architecture search
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Application No.: US16549715Application Date: 2019-08-23
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Publication No.: US11443162B2Publication Date: 2022-09-13
- Inventor: Ming-Hsuan Yang , Xiaojie Jin , Joshua Foster Slocum , Shengyang Dai , Jiang Wang
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Honigman LLP
- Agent Brett A. Krueger
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06N20/00 ; G06F16/901

Abstract:
Methods, and systems, including computer programs encoded on computer storage media for neural network architecture search. A method includes defining a neural network computational cell, the computational cell including a directed graph of nodes representing respective neural network latent representations and edges representing respective operations that transform a respective neural network latent representation; replacing each operation that transforms a respective neural network latent representation with a respective linear combination of candidate operations, where each candidate operation in a respective linear combination has a respective mixing weight that is parameterized by one or more computational cell hyper parameters; iteratively adjusting values of the computational cell hyper parameters and weights to optimize a validation loss function subject to computational resource constraints; and generating a neural network for performing a machine learning task using the defined computational cell and the adjusted values of the computational cell hyper parameters and weights.
Public/Granted literature
- US20210056378A1 RESOURCE CONSTRAINED NEURAL NETWORK ARCHITECTURE SEARCH Public/Granted day:2021-02-25
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