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We present an interactive approach for decompositing bitmap drawings and studio photographs into opaque and semi-transparent vector layers. Semi-transparent layers are especially challenging to extra...
We study the socioeconomic gradient of child development on a sample of low- and middle-income children aged 6–42 months in Bogota using the Bayley Scales of Infant and Toddler Development. We find an...
We study the precision limits of detecting a linear magnetic-field gradient by using W-states in the presence of different types of noises. We consider to use an atomic spin chain for probing the magn...
We consider a class of weighted gradient methods for distributed resource allocation over a network. Each node of the network is associated with a local variable and a convex cost function; the sum of...
We investigated Generalized Gradient Vector Flow Active Contours as a suitable boundary mapping technique for Chromosome spread images which have variability in shape and size, expecting to yield a ro...
Fast gradient methods are known to be non-monotone algorithms, and oscillations typically occur around the solution. To avoid this behavior, we propose in this paper a fast gradient method with restar...
First order optimization methods often perform poorly on ill-conditioned optimization problems. However, by preconditioning the problem data and solving the preconditioned problem, the performance of ...
In this paper, we develop mathematical machinery for verifying that a broad class of general state space Markov chains reacts smoothly to certain types of perturbations in the underlying transition st...
Research exploring the relationship between education and health suggests that people with higher levels of schooling report better health. To emphasize health as a determinant of educational achi...
We present a new continuous adjoint method for Aerodynamic Shape Optimization (ASO) using the Euler equations, which reduces the computational cost of the gradi ents by reducing the volume integral pa...
Large spatial gradients in ionosphere delay are a potentially threatening error source for the Local Area Augmentation System (LAAS). Therefore a better understanding of the ionosphere behavior during...
In complex problems it may, however, be very expensive or infeasible to determine the Hessian matrix A. This motivates quasi-Newton methods which recursively estimate A of A−1 from the measure...
Nowadays, the use of orthophoto in urban areas has become common. It is known that in most parts of urban areas there are a great number of tall buildings which can cause occlusion regions during imag...
In this paper, we consider supervised learning problems such as logistic regression and study the stochastic gradient method with averaging, in the usual stochastic approximation setting where observa...

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