Information Theoretic Combination of Classifiers With Application to Multiple SVMs
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Since the birth of Information Theory, researchers have defined and exploited various information measures, as well as endowed them with operational meanings. Some were born as a "solution to a problem", like Shannon's Entropy and Mutual Information. Other ...
We construct a measure on the thick points of a Brownian loop soup in a bounded domain DD of the plane with given intensity theta>0θ>0, which is formally obtained by exponentiating the square root of its occupation field. The measure is construct ...
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Network information theory studies the communication of information in a network and considers its fundamental limits. Motivating from the extensive presence of the networks in the daily life, the thesis studies the fundamental limits of particular network ...
We present a general approach for online learning and optimal control of manipulation tasks in a supervisory teleoperation context, targeted to underwater remotely operated vehicles (ROVs). We use an online Bayesian nonparametric learning algorithm to buil ...
Chirok is software for a post-refinement test of the absolute structure. The software allows a user to calculate a distribution of the measure of chirality based on intensity quotients and linked to the Flack parameter. The distribution is fitted by a set ...
In this work we study the evolution of the photonic nanojet (PNJ) phenomenon as the ratio of the sphere's diameter over the illumination wavelength changes, for microspheres with diameters from 2 mu m to 100 mu m. We measure the focal point position by usi ...
Device for testing a material response, such as a tissue response, to a compound; said device comprising material impedance measuring means which are adapted to measure the material impedance at the compound action site. ...
The large-scale and granular interaction data collected in online learning platforms such as massive open online courses (MOOCs) provide unique opportunities to better understand individuals' learning processes and could facilitate the design of personaliz ...
In this chapter, we introduce a method for trajectory pattern analysis through the probabilistic inference model with both regional and velocity observations. By embedding Gaussian models into the discrete topic model framework, our method uses continuous ...