A hierarchical information theoretic technique for the discovery of non linear alternative clusterings

2010 ◽  
Author(s):  
Xuan-Hong Dang ◽  
James Bailey
Keyword(s):  
Information Theoretic ◽  
Non Linear ◽  
Theoretic Technique

scholarly journals Entrack: Probabilistic Spherical Regression with Entropy Regularization for Fiber Tractography

2020 ◽  
Author(s):  
Viktor Wegmayr ◽  
Joachim M. Buhmann
Keyword(s):  
Brain Connectivity ◽  
Magnetic Resonance Images ◽  
Probabilistic Methods ◽  
Fiber Tractography ◽  
Information Theoretic ◽  
Spherical Regression ◽  
Theoretic Technique ◽  
White Matter Tractography ◽  
Von Mises

Abstract White matter tractography, based on diffusion-weighted magnetic resonance images, is currently the only available in vivo method to gather information on the structural brain connectivity. The low resolution of diffusion MRI data suggests to employ probabilistic methods for streamline reconstruction, i.e., for fiber crossings. We propose a general probabilistic model for spherical regression based on the Fisher-von-Mises distribution, which efficiently estimates maximum entropy posteriors of local streamline directions with machine learning methods. The optimal precision of posteriors for streamlines is determined by an information-theoretic technique, the expected log-posterior agreement concept. It relies on the requirement that the posterior distributions of streamlines, inferred on retest measurements of the same subject, should yield stable results within the precision determined by the noise level of the data source.

An information theoretic technique to design belief network based expert systems

1996 ◽  
Vol 17 (1) ◽  
pp. 13-30 ◽  
Author(s):  
Sumit Sarkar ◽  
Ram S. Sriram ◽  
Shibu Joykutty ◽  
Ishwar Murthy
Keyword(s):  
Expert Systems ◽  
Information Theoretic ◽  
Belief Network ◽  
Theoretic Technique

scholarly journals Understanding Loneliness in Adolescence: A Test of Competing Hypotheses on the Interplay of Extraversion and Neuroticism

2021 ◽  
Vol 18 (23) ◽  
pp. 12412
Author(s):  
Larissa L. Wieczorek ◽  
Sarah Humberg ◽  
Denis Gerstorf ◽  
Jenny Wagner
Keyword(s):  
Polynomial Regression ◽  
Theoretic Approach ◽  
Cross Sectional ◽  
Information Theoretic ◽  
Open Questions ◽  
Emotional Loneliness ◽  
Non Linear ◽  
One Year ◽  
Information Theoretic Approach ◽  
Main Effects

Given that adolescents often experience fundamental changes in social relationships, they are considered to be especially prone to loneliness. Meanwhile, theory and research highlight that both extraversion and neuroticism are closely intertwined with individual differences in loneliness. Extant research has explored the linear main effects of these personality traits, yet potential non-linear associations (e.g., exponential effects) and the potential interplay of extraversion and neuroticism (e.g., mutual reinforcement effects) remain unknown. We addressed these open questions using cross-sectional and one-year longitudinal data from two adolescent samples (overall N = 583, Mage = 17.57, 60.55% girls) and an information-theoretic approach combined with polynomial regression. Analyses showed little evidence for interaction effects but revealed non-linear effects in addition to the main effects of extraversion and neuroticism on loneliness. For example, the positive cross-sectional association between neuroticism and loneliness was stronger at higher neuroticism levels (i.e., exponential effect). Results differed across loneliness facets in that both traits predicted emotional loneliness, but only extraversion predicted social loneliness. Longitudinal analyses showed that loneliness changes were mainly related to neuroticism. We discuss results in the light of sample differences, elaborate on the importance to differentiate between emotional versus social aspects of loneliness, and outline implications for adolescent development.

scholarly journals A Mathematical Analysis of the Card Game of Betweenies through Kelly's Criterion

2010 ◽  
Vol 2010 ◽  
pp. 1-19
Author(s):  
Konstantinos Drakakis
Keyword(s):  
Mathematical Analysis ◽  
Direct Approach ◽  
Card Game ◽  
Information Theoretic ◽  
The Third ◽  
Theoretic Technique

In the game of Betweenies, the player is dealt two cards out of a deck and bets on the probability that the third card to be dealt will have a numerical value in between the values of the first two cards. In this work, we present the exact rules of the two main versions of the game, and we study the optimal betting strategies. After discussing the shortcomings of the direct approach, we introduce an information-theoretic technique, Kelly's criterion, which basically maximizes the expected log-return of the bet: we offer an overview, discuss feasibility issues, and analyze the strategies it suggests. We also provide some gameplay simulations.

scholarly journals ANALYSIS OF THE TIME EVOLUTION OF NON-LINEAR FINANCIAL NETWORKS

2015 ◽  
Vol 3 (314) ◽  
Author(s):  
Paweł Fiedor
Keyword(s):  
Mutual Information ◽  
Stock Returns ◽  
Time Evolution ◽  
Correlation Coefficient ◽  
Spanning Trees ◽  
Stock Exchange ◽  
Financial Networks ◽  
Information Theoretic ◽  
Non Linear ◽  
Information Theoretic Measures

We treat financial markets as complex networks. It is commonplace to create a filtered graph (usually a Minimally Spanning Tree) based on an empirical correlation matrix. In our previous studies we have extended this standard methodology by exchanging Pearson’s correlation coefficient with information—theoretic measures of mutual information and mutual information rate, which allow for the inclusion of non-linear relationships. In this study we investigate the time evolution of financial networks, by applying a running window approach. Since information—theoretic measures are slow to converge, we base our analysis on the Hirschfeld-Gebelein-Rényi Maximum Correlation Coefficient, estimated by the Randomized Dependence Coefficient (RDC). It is defined in terms of canonical correlation analysis of random non-linear copula projections. On this basis we create Minimally Spanning Trees for each window moving along the studied time series, and analyse the time evolution of various network characteristics, and their market significance. We apply this procedure to a dataset describing logarithmic stock returns from Warsaw Stock Exchange for the years between 2006 and 2013, and comment on the findings, their applicability and significance.

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