blockchain

Deep Research by GeminiApp Revolutionizes AI Learning with Visuals: Charts, Diagrams, and Animations for Enhanced Understanding

According to GeminiApp on Twitter, Deep Research now enhances AI-powered learning by integrating dynamic visuals such as charts, diagrams, and animations. This feature allows users not only to read in ...
IEEE

Vector Quantization-Based Clustered Federated Learning With Global Feature Anchors for Improved Representation and Generalization

Abstract: Clustered federated learning (CFL) addresses the challenge of data heterogeneity in federated learning (FL) by customizing models for different groups of clients. However, existing CFL ...
Business Wire

Elastic Announces Faster Filtered Vector Search with ACORN-1 and Default Better Binary Quantization Compression

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 ...
Scientific Research Publishing

Gersho, A. and Gray, R.M. (2012) Vector Quantization and Signal Compression. Springer Science & Business Media, 159.

ABSTRACT: Breast cancer remains one of the most prevalent diseases that affect women worldwide. Making an early and accurate diagnosis is essential for effective treatment. Machine learning (ML) ...
Scientific Research Publishing

Gray, R. (1984) Vector Quantization. IEEE ASSP Magazine, 1, 4-29.

ABSTRACT: Breast cancer remains one of the most prevalent diseases that affect women worldwide. Making an early and accurate diagnosis is essential for effective treatment. Machine learning (ML) ...
Microsoft

VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models

Scaling model size significantly challenges the deployment and inference of Large Language Models (LLMs). Due to the redundancy in LLM weights, recent research has focused on pushing weight-only ...
IEEE

Power-Efficient Analog Hardware Architecture of the Learning Vector Quantization Algorithm for Brain Tumor Classification

Abstract: This study introduces a design methodology pertaining to analog hardware architecture for the implementation of the learning vector quantization (LVQ) algorithm. It consists of three main ...
marktechpost

Eliminating Vector Quantization: Diffusion-Based Autoregressive AI Models for Image Generation

Autoregressive image generation models have traditionally relied on vector-quantized representations, which introduce several significant challenges. The process of vector quantization is ...
InfoWorld

What is model quantization? Smaller, faster LLMs

Reducing the precision of model weights can make deep neural networks run faster in less GPU memory, while preserving model accuracy. If ever there were a salient example of a counter-intuitive ...