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Recent developments in network neuroscience have highlighted the importance of developing techniques for analysing and modelling brain networks. A particularly powerful approach for studying complex neural systems is to formulate generative models that use ...
Social video sites where people share their opinions and feelings are increasing in popularity. The face is known to reveal important aspects of human psychological traits, so the understanding of how facial expressions relate to personal constructs is a r ...
This paper studies the impact of ambiguity and ambiguity aversion on equilibrium asset prices and portfolio holdings in competitive financial markets. It argues that attitudes toward ambiguity are heterogeneous across the population, just as attitudes towa ...
We consider unicast equation based rate control, where a source estimates the loss event ratio p, and, primarily at loss events, adjusts its sending rate to f(p). Function f is assumed to represent the loss-throughput relation that TCP would experience. Wh ...
Background: Adaptive recovery from stress promotes healthy cognitive affective functioning, whereas maladaptive recovery is linked to poor psychological outcomes. Neural regions, like the anterior cingulate and hippocampus, play critical roles in psychosoc ...
Common factors are omnipresent in everyday life, e.g., people who do well in one cognitive test are likely to perform well in other cognitive tests as well, and vice versa. In vision, however, there seems to be a multitude of specific factors rather than a ...
This thesis focuses on the route choice behavior of car drivers (uni-modal networks). More precisely, we are interested in identifying which route a given traveler would take to go from one location to another. For the analysis of this problem we use discr ...
We consider unicast equation based rate control, where a source estimates the loss event ratio p, and, primarily at loss events, adjusts its sending rate to f(p). Function f is assumed to represent the loss-throughput relation that TCP would experience. Wh ...
Complexity is a double-edged sword for learning algorithms when the number of available samples for training in relation to the dimension of the feature space is small. This is because simple models do not sufficiently capture the nuances of the data set, ...
