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

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 ...

New capabilities deliver up to 5X faster filtered vector search, improved ranking quality, and lower infrastructure costs to unlock scalable, cost-efficient AI applications SAN FRANCISCO, July 30, ...

Recursive marginal quantization (RMQ) allows the construction of optimal discrete grids for approximating solutions to stochastic differential equations in d dimensions. Product Markovian quantization ...