We study whether a multivariate Lévy-driven moving average process can shadow arbitrarily closely any continuous path, starting from the present value of the process, with positive conditional probability, which we call the conditional small ball property. Our main results establish the conditional small ball property for Lévy-driven moving average processes under natural non-degeneracy conditi...

We estimate a model of strategic voting with incomplete information in which committee members – judges in the US courts of appeals – have the opportunity to communicate before casting their votes. The model is characterized by multiple equilibria, and partial identification of model parameters. We obtain confidence regions for these parameters using a two-step estimation procedure that allows ...

introduction. the basic science exam is conducted, two times each year and, success in this exams is an essential condition for medical students to continue their education in medicine. this descriptive research was designed to study the relationship between some variables, including age, sex, place of stay, conditional history and results of basic science exams. methods. this study was impleme...

It is well established that the notion of min-entropy fails to satisfy the chain rule of the form H(X,Y ) = H(X|Y )+ H(Y ), known for Shannon Entropy. The lack of a chain rule causes a lot of technical difficulties, particularly in cryptography where the chain rule would be a natural way to analyze how min-entropy is split among smaller blocks. Such problems arise for example when constructing ...

In this paper, we address the challenge of creating accurate and robust partof-speech taggers for low-resource languages. We propose a method that leverages existing parallel data between the target language and a large set of resourcerich languages without ancillary resources such as tag dictionaries. Crucially, we use CCA to induce latent word representations that incorporate cross-genre dist...

Our work addresses automatic detection of enunciations and segments with reformulations in French spoken corpora. The proposed approach is syntagmatic. It is based on reformulation markers and specificities of spoken language. The reference data are built manually and have gone through consensus. Automatic methods, based on rules and CRF machine learning, are proposed in order to detect the enu...

The problem of transmission scheduling over a correlated time-varying wireless channel is formulated as a Constrained Markov Decision Process. The model includes a transmission buffer and finite state Markov model for time-varying radio channel and incoming traffic. The resulting cross-layer optimization problem is formulated to minimize the transmission cost under the constraint on a buffer co...

In this paper, we have examined 4 models for Great Salt Lake level forecasting: ARMA (Auto-Regression and Moving Average), ARFIMA (Auto-Regressive Fractional Integral and Moving Average), GARCH (Generalized Auto-Regressive Conditional Heteroskedasticity) and FIGARCH (Fractional Integral Generalized Auto-Regressive Conditional Heteroskedasticity). Through our empirical data analysis where we div...