Invention Application
- Patent Title: ENCODING TECHNIQUES FOR NEURAL NETWORK ARCHITECTURES
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Application No.: US17194077Application Date: 2021-03-05
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Publication No.: US20220284282A1Publication Date: 2022-09-08
- Inventor: Pavan Kumar Vitthaladevuni , Taesang Yoo , Naga Bhushan , June Namgoong
- Applicant: QUALCOMM Incorporated
- Applicant Address: US CA San Diego
- Assignee: QUALCOMM Incorporated
- Current Assignee: QUALCOMM Incorporated
- Current Assignee Address: US CA San Diego
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04

Abstract:
Methods, systems, and devices for wireless communications are described. A user equipment (UE) may receive an indication of one or more encoding operations to use for encoding a compressed dataset, the one or more encoding operations including a differential encoding operation, or an entropy encoding operation, or both. In some examples, using a neural network, the UE may first encode a dataset based on an additional encoding operation to generate a compressed dataset and then quantize the compressed dataset encoded based on the additional encoding operation. Subsequently, after the dataset has been initially encoded and then quantized, the UE may use the indication of the one or more encoding operations to further encode and compress the dataset. The UE may then transmit the dataset to a second device based on the one or more encoding operations.
Information query