公开(公告)号：US20240160892A1

公开(公告)日：2024-05-16

申请号：US18414068

申请日：2024-01-16

Applicant: samsung electronics co., ltd.

Inventor： Prateek KESERWANI ,  Srinivas Soumitri MIRIYALA ,  Vikram Nelvoy RAJENDIRAN ,  Pradeep NELAHONNE SHIVAMURTHAPPA

IPC: G06N3/04

CPC classification number: G06N3/04

Abstract: A method for selecting an artificial intelligence (AI) model in neural architecture search, includes: measuring a scale of receptive field for a plurality of neural network layers corresponding to each of a plurality of candidate AI models; determining a first score for a first group of neural network layers among the plurality of neural network layers based on the scale of the receptive field for the first group of neural network layers, the scale of the receptive field for each of the first group of neural network layers being smaller than a size of an object; determining a second score for a second group of neural network layers among the plurality of neural network layers based on the scale of the receptive field for the second group of neural network layers, the scale of the receptive field for each of the second group of neural network layers being greater than the size of the object; determining a third score for each of the plurality of candidate AI models as a function of the first score and the second score; and selecting, based on the third score, a candidate AI model among the plurality of candidate AI models for training and deployment, the candidate AI model having a highest third score among the third scores of the plurality of candidate AI models.

公开(公告)号：US20240242060A1

公开(公告)日：2024-07-18

申请号：US18415261

申请日：2024-01-17

Applicant: SAMSUNG ELECTRONICS CO.,LTD.

Inventor： Srinivas Soumitri MIRIYALA ,  Ashutosh Pavagada VISWESWARA ,  Suhas P K ,  Vikram Nelvoy RAJENDIRAN

IPC: G06N3/04

CPC classification number: G06N3/04

Abstract: According to an embodiment of the disclosure, a method may include providing, by the electronic device, a plurality of Pareto fronts based on at least two performance parameters. The method may include identifying, by the electronic device, an optimal Pareto front from among the plurality of Pareto fronts. The method may include providing, by the electronic device, a second AI model iteratively. The method may include identifying, by the electronic device, whether the second AI model belongs to the optimal Pareto front. The method may include identifying, by the electronic device, the at least two performance parameters corresponding to the second AI model based on identifying that the second AI model belongs to the optimal Pareto front. The method may include obtaining, by the electronic device, the second AI model based on identifying that the second AI model meets one or more predetermined performance parameters.

公开(公告)号：US20240232587A1

公开(公告)日：2024-07-11

申请号：US18429690

申请日：2024-02-01

Applicant: Samsung Electronics Co., Ltd.

Inventor： Srinivas Soumitri MIRIYALA ,  Efthymia TSAMOURA ,  Shah Ayub QUADRI ,  Vikram Nelvoy RAJENDIRAN ,  Venkappa MALA

IPC: G06N3/047 ,  G06N7/01

CPC classification number: G06N3/047 ,  G06N7/01

Abstract: A method and an electronic device for neuro-symbolic learning of an artificial intelligence (AI) model are provided. The method includes receiving input data including various contents and determining in an output of the AI model a predicted probability for each of the contents of the input data, determining a neural loss of the AI model by comparing the predicted probability with a predefined desired probability, determining a symbolic loss for the AI model by comparing the predicted probability with a pre-determined undesired probability, determining weights of a plurality of layers of the AI model, and updating the weights of the plurality of layers of the AI model based on the neural loss and the symbolic loss.