Recently, it is recognized that nonlinear relationships among latent variables in a structural equation model are important. In this article, maximum likelihood (ML) analysis of a general nonlinear structural equation model that contains 5xed covariates in the measurement equation and the nonlinear structural equation is investigated. A MCEM algorithm is implemented to obtain the ML estimates, ...

The conditional value at risk (CVaR) is a popular risk measure which enables risk-averse decision making under uncertainty. We consider maximizing the CVaR of a continuous submodular function, an extension of submodular set functions to a continuous domain. One example application is allocating a continuous amount of energy to each sensor in a network, with the goal of detecting intrusion or co...

We aim at learning an unbiased stochastic edit distance in the form of a finite-state transducer from a corpus of (input,output) pairs of strings. Contrary to the other standard methods, which generally use the algorithm Expectation Maximization, our algorithm learns a transducer independently on the marginal probability distribution of the input strings. Such an unbiased way to proceed require...

This paper presents a semi-supervised training method for linear-chain conditional random fields that makes use of labeled features rather than labeled instances. This is accomplished by using generalized expectation criteria to express a preference for parameter settings in which the model’s distribution on unlabeled data matches a target distribution. We induce target conditional probability ...

The study of social processes by which ideas and innovations diffuse through social networks has been ongoing for more than half a century and as a result a fair understanding of such processes has been achieved. Modern models of social influence have been augmented with various features allowing for arbitrary network structure, non-uniform interactions, probabilistic events and other aspects. ...

This note studies the impact on the adjustment process of Uruguayan manufacturing firms’ capital, and unskilled and skilled labor demands associated with increasing import penetration from China and India. The adjustment process is defined as the percentage of the gap between desired (optimal) and actual factor employment levels closed by the firm. Desired factor levels are obtained from a coun...

In this paper usefulness of quasi-Newton iteration procedure in parameters estimation of the conditional variance equation within BHHH algorithm is presented. Analytical solution of maximization of the likelihood function using first and second derivatives is too complex when the variance is time-varying. The advantage of BHHH algorithm in comparison to the other optimization algorithms is that...

Sources Hichem Snoussi and Ali Mohammad-Djafari Laboratoire des Signaux et Systèmes (L2S), Supélec, Plateau de Moulon, 91192 Gif-sur-Yvette Cedex, France Abstract. In this contribution, we consider the problem of source separation in the case of noisy instantaneous mixtures. In a previous work [1], sources have been modeled by a mixture of Gaussians leading to an hierarchical Bayesian model by ...

This paper considers the problem of source separation in the case of noisy instantaneous mixtures. In a previous work [1], sources have been modeled by a mixture of Gaussians leading to an hierarchical Bayesian model by considering the labels of the mixture as i.i.d hidden variables. We extend this modelization to incorporate a Markovian structure for the labels. This extension is important for...