Visual Studio Magazine

Support Vector Regression with SGD Training Using C#

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.
IEEE

High-Speed Channel Modeling With Machine Learning Methods for Signal Integrity Analysis

Abstract: In this work, machine learning methods are applied to high-speed channel modeling for signal integrity analysis. Linear, support vector, and deep neural network (DNN) regressions are adopted ...
IEEE

Nonparameter Nonlinear Phase Noise Mitigation by Using M-ary Support Vector Machine for Coherent Optical Systems

Abstract: The M-ary support vector machine (SVM) is introduced as a nonparameter nonlinear phase noise (NLPN) mitigation approach for the coherent optical systems. The NLPN tolerance of the system can ...
GitHub

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

Vector Post-Training Quantization (VPTQ) is a novel Post-Training Quantization method that leverages Vector Quantization to high accuracy on LLMs at an extremely low bit-width (<2-bit). VPTQ can ...
GitHub

Python-based Advanced Numerical Nonlinear Optimization for Radiotherapy

Dataset import and preprocessing Automatic feature map generation 27-type feature catalogue for iterative (re)calculation to support model integration into optimization 7 customizable internal model ...
Forbes

The Rise Of Vector Databases

LONDON, ENGLAND - AUGUST 19: Workers clean the East-facing clock face of the Elizabeth Tower of the Houses of Parliament on August 19, 2014 in London, England. Workers are cleaning the four faces of ...