Any announcement from the Federal Reserve has a huge impact on the interest rate markets. The press releases from the Federal Open Market Committee (FOMC) are major inputs to the market and the random intervention model is applied to interest rate futures transaction data to measure FOMC announcement impact. Missing prices during non-trading time periods are imputed iteratively during the estim...

We propose a neural network-based technique for enhancing the quality of audio signals such as speech or music by transforming inputs encoded at low sampling rates into higher-quality signals with an increased resolution in the time domain. This amounts to generating the missing samples within the low-resolution signal in a process akin to image super-resolution. On standard speech and music da...

Learning over multi-view data is a challenging problem with strong practical applications. Most related studies focus on the classification point of view and assume that all the views are available at any time. We consider an extension of this framework in two directions. First, based on the BiGAN model, the Multi-view BiGAN (MV-BiGAN) is able to perform density estimation from multi-view input...

Learning over multi-view data is a challenging problem with strong practical applications. Most related studies focus on the classification point of view and assume that all the views are available at any time. We consider an extension of this framework in two directions. First, based on the BiGAN model, the Multi-view BiGAN (MV-BiGAN) is able to perform density estimation from multi-view input...

This paper deals with the problem of synchronization of chaotic dynamical systems. We consider a drive-response type of synchronization via a scalar transmitted signal. Unlike most works we consider the presence of some unknown inputs in the drive system and that no knowledge about their nature is available. A reduced-order observer-based response system is designed to synchronize with the miss...

A two-layer neural network is developed in which the neuron model computes a user-defined similarity function between inputs and weights. The neuron model is formed by the composition of an adapted logistic function with the mean of the partial input-weight similarities. The model is capable of dealing directly with variables of potentially different nature (continuous, ordinal, categorical); t...

An identification problem with no a priori separation of the variables into inputs and outputs and representation invariant approximation criterion is considered. The model class consists of linear time-invariant systems of bounded complexity and the approximation criterion is the minimum of a weighted 2-norm distance between the given time series and a time series that is consistent with the m...

Large-scale natural language generation requires the integration of vast amounts of knowledge: lexical, grammatical, and conceptual. A robust generator must be able to operate well even when pieces of knowledge are missing. It must also be robust against incomplete or inaccurate inputs. To attack these problems, we have built a hybrid generator , in which gaps in symbolic knowledge are lled by ...

a case of multiple pulp stones, a supernumerary tooth and a congenitally missed tooth accompanied by several developmental dental anomalies concurrently affect- ing the upper and lower anterior teeth in an iranian healthy girl is reported. devel- opmental tooth abnormalities are usually found in conjunction with certain diseases or conditions. in the present case, although the patient had consa...

The Tools for Operations Planning (TOPL) employs the Link-Node Cell Transmission model for macroscopic freeway traffic simulations for specifying operational strategies like ramp metering, demand and incident management.Traffic flow and occupancy data from loop detectors is used for calibrating these models and specifying the inputs to the simulation. However, flow data from ramps are often to ...