This repository supports HAAG research efforts in developing new vector quantization and compression methods, and benchmarking them against existing open-source and private-industry methods. TBD: As ...

Vector quantisation and its associated learning algorithms form an essential framework within modern machine learning, providing interpretable and computationally efficient methods for data ...

Abstract: Vector quantization is a nearest neighbor representation based compression technique for vector data. It creates a collection of codewords to represent the entire vector space. Each vector ...

This project is a comprehensive implementation of a semantic search and recommendation system using the Qdrant vector database. It is designed to process large datasets, generate vector embeddings, ...

Abstract: A broad range of technologies rely on remote inference, wherein data acquired is conveyed over a communication channel for inference in a remote server. Communication between the ...

This is a preview. Log in through your library . Abstract Recent results in quantization theory show that the mean-squared expected distortion can reach a rate of convergence of O(1/n), where n is the ...

SAN FRANCISCO--(BUSINESS WIRE)--Elastic (NYSE: ESTC), the Search AI Company, announced new performance and cost-efficiency breakthroughs with two significant enhancements to its vector search. Users ...

Now-a-days, data on the web is increasing like water in the ocean. Big data is one of the emerging areas that deal with large velocity of data. “Big data is not defined in single world data sets that ...