We present a new form of least squares (LS), called “hyperLS”, for geometric problems that frequently appear in computer vision applications. Doing rigorous error analysis, we...
Abstract. We present a survey of recent results concerning the theoretical and empirical performance of algorithms for learning regularized least-squares classifiers. The behavior ...
The analysis of online least squares estimation is at the heart of many stochastic sequential decision-making problems. We employ tools from the self-normalized processes to provi...
This paper proposes a reweighted least squares algorithm for quadrature amplitude modulation (QAM) detector in multiple-input multiple-output (MIMO) channels. Although the QAM det...