We consider the graphical lasso formulation for estimating a Gaussian graphical model in the high-dimensional setting. This approach entails estimating the inverse covariance matrix under a multivariate normal model by maximizing the 1-penalized log-likelihood. We present a very simple necessary and sufficient condition that can be used to identify the connected components in the graphical lass...

Belief Propagation algorithms are instruments used broadly to solve graphical model optimization and statistical inference problems. In the general case of a loopy Graphical Model, Belief Propagation is a heuristic which is quite successful in practice, even though its empirical success, typically, lacks theoretical guarantees. This paper extends the short list of special cases where correctnes...

Mobile cameras are being used now-a-days to scan barcodes to retrieve the product details. But the drawback is mobile cameras are made by a charge coupled device which is does not have the ability to handle out of focus and blur images. In this project, out of focus and blur images are restored using a dynamic template matching algorithm using directed graphical model. The directed graphical mo...

1 Palombini BC, Villanova CAC, Araujo E, et al. A pathogenic triad in chronic cough. Chest 1999; 116:279–284 2 Irwin RS, Corrao WM, Pratter RM. Chronic cough: the spectrum and frequency of causes, key components of diagnostic evaluation, and outcome of specific therapy. Am Rev Respir Dis 1990; 141:640–647 3 Pratter MR, Bartter T, Akers S, et al. An algorithmic approach to chronic cough. Ann Int...

Symmetric graphs, such as the n-dimensional Boolean hypercube Qn, and the cube-connected cycles, have been widely used as processor or communication interconnection networks. For designing, analyzing and improving such networks, Akers and Krishnamurthy proposed a formal grouptheoretic model in [1]. Based on the model, the n-dimensional bubble-sort graph is proposed as one of those classes of ne...

It is well known that an arbitrary graphical model of statistical inference defined on a tree, i.e. on a graph without loops, is solved exactly and efficiently by an iterative Belief Propagation (BP) algorithm convergent to unique minimum of the so-called Bethe free energy functional. For a general graphical model on a loopy graph the functional may show multiple minima, the iterative BP algori...

We consider the problem of Ising and Gaussian graphical model selection given n i.i.d. samples from the model. We propose an efficient threshold-based algorithm for structure estimation based on conditional mutual information thresholding. This simple local algorithm requires only loworder statistics of the data and decides whether two nodes are neighbors in the unknown graph. We identify graph...

Although numerous studies have attempted to understand the causes of various forms of police misconduct, there is still no clear theoretical explanation of police misbehavior. Akers’ social learning theory posits that peer associations, attitudes, reinforcement, and modeling are predictors of delinquency and crime in general. With this article, we seek to determine if the theory can account for...