Hackaday

TurboQuant: Reducing LLM Memory Usage With Vector Quantization

Large language models (LLMs) aren’t actually giant computer brains. Instead, they are effectively massive vector spaces in ...
Open Heart

Periprocedural evaluation of patients with BAV stenosis undergoing TAVR: a machine learning-based study

Background Transcatheter aortic valve replacement (TAVR) has increasingly emerged as one of the primary treatments for ...
Scientific Research Publishing

Efficiency of Classification Algorithms in Monitoring Land Use through Remote Sensing in Sissili Province of Burkina Faso ()

Monitoring of natural resources is a major challenge that remote sensing tools help to facilitate. The Sissili province in Burkina Faso is a territory that includes significant areas dedicated for the ...

Health Discovery Corp.

Health Discovery Corp. company and executive profile by Barron's. View the latest HDVY company infomation and executive bios.
IEEE

Support Vector Machine Algorithm in Machine Learning

Abstract: The Support Vector methods was proposed by V.Vapnik in 1965, when he was trying to solve problems in pattern recognition. In 1971, Kimeldorf proposed a method of constructing kernel space ...
Scientific Research Publishing

Hybrid Software Model for Defect Detection and Cost Evaluation Using Support Vector Machine Algorithm ()

Software defect prediction and cost estimation are critical challenges in software engineering, directly influencing software quality and project management efficiency. This study presents a ...
Frontiers

Enhancing performance prediction of municipal solid waste generation: a strategic management

Municipal Solid Waste Generation (MSWG) presents a significant challenge for sustainable urban development, with waste production escalating at alarming rates worldwide. To address this issue, ...
IEEE

Khatri-Rao Factorization Based Bi-Level Support Vector Machine for Hyperspectral Image Classification

Abstract: As a benchmark supervised learning algorithm, support vector machine (SVM) has drawn much attention and reported plenty of impressive results in hyperspectral images (HSIs) classification.