In this tutorial we give an overview of the basic ideas underlying Support Vector (SV)
machines for function estimation. Furthermore, we include a summary of currently used …

Interior Point Methods for Linear Optimization is a comprehensive, thorough textbook on
interior point methods (IPMs). The era of IPMs was initiated by N. Karmarkar's 1984 paper …

We present a general-purpose solver for convex quadratic programs based on the
alternating direction method of multipliers, employing a novel operator splitting technique …

This paper introduces HPIPM, a high-performance framework for quadratic programming
(QP), designed to provide building blocks to efficiently and reliably solve model predictive …

Sparse representation has attracted much attention from researchers in fields of signal
processing, image processing, computer vision, and pattern recognition. Sparse …

Constrained spherical deconvolution (CSD) has become one of the most widely used
methods to extract white matter (WM) fibre orientation information from diffusion-weighted …

The emergence of mobile edge computing (MEC) and unmanned aerial vehicles (UAVs) is
of great significance for the prospective development of Internet of Things (IoT). The …

A bstract We introduce SDPB: an open-source, parallelized, arbitrary-precision semidefinite
program solver, designed for the conformal bootstrap. SDPB significantly outperforms less …

The inconsistency between textual features and visual contents can cause poor image
search results. To solve this problem, click features, which are more reliable than textual …

Inverse problems arise from the need to interpret indirect and incomplete measurements. As
an area of contemporary mathematics, the field of inverse problems is strongly driven by …