Knowledge Generated Our study developed and validated a support vector machine learning algorithm to yield variant calls for all 114 biomarkers analyzed with 95% limit of detection 0.19% for cfDNA ...

The lessons from Recentive are clear: training a machine-learning model, by itself, is not enough to move a claim beyond abstraction; listing well-known models like neural networks or support ...

Opinion: Lidiya Mishchenko and Pooya Shoghi explain how to bridge a gap preventing successful patent claims to protect new developments for machine learning algorithms.

The increased rate of data collection relating to athlete load has led to interest in machine learning (ML) approaches for sports data analysis, including injury risk prediction. Prior reviews have ...

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 based on ...

Accelerated Incremental Learning with Support vector Machines This Thesis aims to investigate the possibility of implementing the SVM algorithm on an embedded SoC with changes to the algorithm ...

This repository contains an efficient implementation of Survival Support Vector Machines as proposed in Pölsterl, S., Navab, N., and Katouzian, A., Fast Training of Support Vector Machines for ...