We tackle deconvolution of motion blur in hand-held consumer photography with a Bayesian framework combining sparse gradient and color priors for regularization. We develop a closed-form optimization utilizing iterated re-weighted least squares (IRLS) with a Gaussian approximation of the regularization priors. The model parameters of the priors can be learned from a set of natural images which ...

Background: The prevalence of restless legs syndrome (RLS) is approximately 10% in general population. This condition is more prevalent in certain diseases and we previously reported the prevalence of RLS in chronic liver disease population to be 62%. Objectives: Our aim was to assess the self-reported prevalence of RLS using an RLS symptom specific questionnaire in liver transplant patients. M...

In a semi-supervised learning scenario, (possibly noisy) partially observed labels are used as input to train a classifier, in order to assign labels to unclassified samples. In this paper, we construct a complete graph-based binary classifier given only samples’ feature vectors and partial labels. Specifically, we first build appropriate similarity graphs with positive and negative edge weight...

Multiple task learning (MTL) is becoming popular due to its theoretical advances and empirical successes. The key idea of MTL is to explore the hidden relationships among multiple tasks to enhance learning performance. Recently, many MTL algorithms have been developed and applied to various problems such as feature selection and kernel learning. However, most existing methods highly relied on c...

1) Study's objective is "To assess rotigotine transdermal patch for the perioperative management of moderate to severe RLS". To assess what? Efficacy? Feasibility of use? The objective of this posthoc analysis was to assess the feasibility of use of rotigotine transdermal patch for the perioperative management of moderate to severe RLS. Efficacy data for the entire study population, including p...

OBJECTIVE To evaluate the frequency, severity, and risk factors for restless legs syndrome (RLS) in healthcare personnel. METHODS This cross-sectional study was performed at the Outpatient Family Medicine Clinic of Meram Medical Faculty in Konya, Turkey and included 354 healthcare personnel who were working at the Meram Medical Faculty Hospital between October 2010 and June 2011. The Internat...

Based on minimizing a piecewise diierentiable lp function subject to a single inequality constraint, this paper discusses algorithms for a discretized regularization problem for ill-posed inverse problems. We examine computational challenges of solving this regularization problem. Possible minimization algorithms such as the steepest descent method, iteratively weighted least squares (IRLS) met...

Minority class detection is the problem of detecting the occurrence of rare key events differing from the majority of a data set. This paper considers the problem of unsupervised minority class detection for multidimensional data that are highly nongaussian, mixed (continuous and/or discrete), noisy, and nonlinearly related, such as occurs, for example, in fraud detection in typical financial d...

Standard formulations of image/signal deconvolution under wavelet-based priors/regularizers lead to very high-dimensional optimization problems involving the following difficulties: the non-Gaussian (heavy-tailed) wavelet priors lead to objective functions which are nonquadratic, usually nondifferentiable, and sometimes even nonconvex; the presence of the convolution operator destroys the separ...