Search results for "Intelligence"
showing 10 items of 6959 documents
Dimensionality reduction via regression on hyperspectral infrared sounding data
2014
This paper introduces a new method for dimensionality reduction via regression (DRR). The method generalizes Principal Component Analysis (PCA) in such a way that reduces the variance of the PCA scores. In order to do so, DRR relies on a deflationary process in which a non-linear regression reduces the redundancy between the PC scores. Unlike other nonlinear dimensionality reduction methods, DRR is easy to apply, it has out-of-sample extension, it is invertible, and the learned transformation is volume-preserving. These properties make the method useful for a wide range of applications, especially in very high dimensional data in general, and for hyperspectral image processing in particular…
The Three Steps of Clustering In The Post-Genomic Era
2013
This chapter descibes the basic algorithmic components that are involved in clustering, with particular attention to classification of microarray data.
A Feature Set Decomposition Method for the Construction of Multi-classifier Systems Trained with High-Dimensional Data
2013
Data mining for the discovery of novel, useful patterns, encounters obstacles when dealing with high-dimensional datasets, which have been documented as the "curse" of dimensionality. A strategy to deal with this issue is the decomposition of the input feature set to build a multi-classifier system. Standalone decomposition methods are rare and generally based on random selection. We propose a decomposition method which uses information theory tools to arrange input features into uncorrelated and relevant subsets. Experimental results show how this approach significantly outperforms three baseline decomposition methods, in terms of classification accuracy.
Regularized Regression Incorporating Network Information: Simultaneous Estimation of Covariate Coefficients and Connection Signs
2014
We develop an algorithm that incorporates network information into regression settings. It simultaneously estimates the covariate coefficients and the signs of the network connections (i.e. whether the connections are of an activating or of a repressing type). For the coefficient estimation steps an additional penalty is set on top of the lasso penalty, similarly to Li and Li (2008). We develop a fast implementation for the new method based on coordinate descent. Furthermore, we show how the new methods can be applied to time-to-event data. The new method yields good results in simulation studies concerning sensitivity and specificity of non-zero covariate coefficients, estimation of networ…
Bayesian versus data driven model selection for microarray data
2014
Clustering is one of the most well known activities in scientific investigation and the object of research in many disciplines, ranging from Statistics to Computer Science. In this beautiful area, one of the most difficult challenges is a particular instance of the model selection problem, i.e., the identification of the correct number of clusters in a dataset. In what follows, for ease of reference, we refer to that instance still as model selection. It is an important part of any statistical analysis. The techniques used for solving it are mainly either Bayesian or data-driven, and are both based on internal knowledge. That is, they use information obtained by processing the input data. A…
Co-construct territorial cultures
2015
International audience; Carrying out investigations in the framework of the scientific network INTI (International Network of Territorial Intelligence, http://inti.hypotheses.org/), the main idea is here to value the contribution of multiple approaches in territorial information and communication science that can be experienced there. Inspired by the triad of Pestalozzi, these experiences have applied and adapted the territorial engineering approach "Catalyse" in their territories.From the cooperative structuring of information to concrete initiatives of local change, communication processes make possible iterations between understanding and action, in which the analysis of the effects of s…
Gender differences in internet addiction: A study on variables related to its possible development
2023
Internet addiction and its related variables (i.e., internet gaming addiction, social media addiction, fear of missing out, phubbing) have mostly been investigated in the general population without considering possible gender differences. The present study aimed to investigate the specific characteristics of men and women in the possible development of pathological behaviors related to internet addiction. A total of 276 participants (of ages ranging from 18 to 30 years old) were recruited in the study (46.7% were males) and responded to online questionnaires on variables related to internet addiction and psychological traits. The results showed that gender represents a key factor in explain…
Neural networks with non-uniform embedding and explicit validation phase to assess Granger causality
2015
A challenging problem when studying a dynamical system is to find the interdependencies among its individual components. Several algorithms have been proposed to detect directed dynamical influences between time series. Two of the most used approaches are a model-free one (transfer entropy) and a model-based one (Granger causality). Several pitfalls are related to the presence or absence of assumptions in modeling the relevant features of the data. We tried to overcome those pitfalls using a neural network approach in which a model is built without any a priori assumptions. In this sense this method can be seen as a bridge between model-free and model-based approaches. The experiments perfo…
Active spike transmission in the neuron model with a winding threshold manifold
2012
International audience; We analyze spiking responses of excitable neuron model with a winding threshold manifold on a pulse stimulation. The model is stimulated with external pulse stimuli and can generate nonlinear integrate-and-fire and resonant responses typical for excitable neuronal cells (all-or-none). In addition we show that for certain parameter range there is a possibility to trigger a spiking sequence with a finite number of spikes (a spiking message) in the response on a short stimulus pulse. So active transformation of N incoming pulses to M (with M>N) outgoing spikes is possible. At the level of single neuron computations such property can provide an active "spike source" comp…
Parental Stress and ASD
2016
The objectives of this study were (a) to evaluate parental stress in parents of children with autism spectrum disorders (ASD group) and compare it with the stress in parents of children with typical development (comparison group); (b) to study the relationship between parental stress, autism severity, and both verbal and performance IQ; and (c) to study the relationship between parental stress and resilience. Parental stress in the ASD group was clinically significant and higher than in the comparison group. The child’s autism severity was a significant predictor of parental stress related to the child’s distractibility and hyperactivity. The child’s verbal IQ was a significant predictor o…