公开(公告)号：US20250111213A1

公开(公告)日：2025-04-03

申请号：US18844254

申请日：2023-05-01

Applicant: Visa International Service Association

Inventor： Huiyuan Chen ,  Xiaoting Li ,  Michael Yeh ,  Yan Zheng ,  Hao Yang

IPC: G06N3/0495 ,  G06N3/084

Abstract: Systems, methods, and computer program products are provided for saving memory during training of knowledge graph neural networks. The method includes receiving a training dataset including a first set of knowledge graph embeddings associated with a plurality of entities for a first layer of a knowledge graph, inputting the training dataset into a knowledge graph neural network to generate at least one further set of knowledge graph embeddings associated with the plurality of entities for at least one further layer of the knowledge graph, quantizing the at least one further set of knowledge graph embeddings to provide at least one set of quantized knowledge graph embeddings, storing the at least one set of quantized knowledge graph embeddings in a memory, and dequantizing the at least one set of quantized knowledge graph embeddings to provide at least one set of dequantized knowledge graph embeddings.

公开(公告)号：US20240412098A1

公开(公告)日：2024-12-12

申请号：US18330122

申请日：2023-06-06

Applicant: Visa International Service Association

Inventor： Hanqing Chao ,  Yuhang Wu ,  Xiaoting Li ,  Hongyi Liu ,  Kwei-Herng Lai ,  Linyun He ,  Shubham Agrawal ,  Mahashweta Das ,  Hao Yang

IPC: G06N20/00 ,  G06F17/14

Abstract: Methods and systems are provided for synthesizing realistic time series data that may be used to better identify outliers within the synthesized realistic time series data. Noise can be introduced to a time domain representation of time series data and can introduce noise to a frequency domain representation of the time series data. Further, labeled anomalous points can be inserted into the time series data. The time series data may then be used for training a machine learning model to identify anomalies within new time series data.