Google's new multi-vector retrieval algorithm (MUVERA) improves search speed and performs better on complex queries.

Support vector machines are a family of data analysis algorithms based on convex quadratic programming. We focus on their use for classification: in that case, the SVM algorithms work by maximizing ...

Support Vector Machines (SVMs) are a powerful and versatile supervised machine learning algorithm primarily used for classification and regression tasks. They excel in high-dimensional spaces and are ...

Support Vector Machine (SVM) is often used in regression and classification problems. However, SVM needs to find proper kernel function to solve high-dimensional problems. We propose an improved ...

Abstract The manuscript presents an augmented Lagrangian—fast projected gradient method (ALFPGM) with an improved scheme of working set selection, pWSS, a decomposition based algorithm for training ...

The support vector machine algorithm’s objective is to find a hyperplane in an N-dimensional space that distinctly classifies the data points. In SVM, we plot each data point in the dataset in an ...