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We propose a randomized block-coordinate variant of the classic Frank-Wolfe algorithm for convex optimization with block-separable constraints. Despite its lower iteration cost, we show that it achieves a similar convergence rate in duality gap as the full Frank-Wolfe algorithm. We also show that, when applied to the dual structural support vector machine(More)
The Alzheimer's Disease Neuroimaging Initiative (ADNI) beginning in October 2004, is a 6-year research project that studies changes of cognition, function, brain structure and function, and biomarkers in elderly controls, subjects with mild cognitive impairment, and subjects with Alzheimer's disease (AD). A major goal is to determine and validate MRI, PET(More)
UNLABELLED (11)C-ABP688 is a new PET ligand to assess the subtype 5 metabotropic glutamate receptor (mGlu(5)). The purpose of this study was to evaluate different methods for the analysis of human (11)C-ABP688 data acquired from 6 healthy, young volunteers. METHODS The methods were a 1-tissue-compartment model (K(1), k(2)''), a 2-tissue-compartment model(More)
In this paper we review and compare state-of-the-art optimization techniques for solving the problem of minimizing a twice-differentiable loss function subject to 1-regularization. The first part of this work outlines a variety of the approaches that are available to solve this type of problem, highlighting some of their strengths and weaknesses. In the(More)
1 Smooth L1-norm aproximation In order to deal with the non-differentiable penalty, we propose a smooth approximation to the L1 penalty based on the following: (i) |x| = (x) + + (−x) + , where the plus function is (x) + = max {x, 0} (ii) The plus function can be approximated (smoothly)[2], by the integral to a smooth approximation of the sigmoid function:(More)
UNLABELLED 3-(6-Methyl-pyridin-2-ylethynyl)-cyclohex-2-enone-O-11C-methyl-oxime (11C-ABP688), a noncompetitive and highly selective antagonist for the metabotropic glutamate receptor subtype 5 (mGluR5), was evaluated for its potential as a PET agent. METHODS Six healthy male volunteers (mean age, 25 y; range, 21-33 y) were studied. Brain perfusion(More)
BACKGROUND Reduced reward learning might contribute to the onset and maintenance of major depressive disorder (MDD). In particular, the inability to utilize rewards to guide behavior is hypothesized to be associated with anhedonia, a core feature and potential trait marker of MDD. Few studies have investigated whether reduced reward learning normalizes with(More)
In this paper, we present the DelayLyzer which is a tool for the calculation of delay bounds using network calculus. It respects the specics of Industrial Ethernet by implementing not only STP and RSTP but also MRP as forwarding mechanism. The tool allows to specify failure scenarios and alternate forwarding protocols for which delay bounds can also be(More)