Different researchers hold different views of what the term meta-learning exactlymeans. The
first part of this paper provides our own perspective view in which the goal isto build self …

Network theory provides an intuitively appealing framework for studying relationships
among interconnected brain mechanisms and their relevance to behaviour. As the space of …

Ming Li Paul Vitányi Fourth Edition Page 1 An Introduction to Kolmogorov Complexity and Its
Applications Ming Li Paul Vitányi Fourth Edition Texts in Computer Science Page 2 Texts in …

Interestingness measures play an important role in data mining, regardless of the kind of
patterns being mined. These measures are intended for selecting and ranking patterns …

Personal motivation. The dream of creating artificial devices that reach or outperform human
inteUigence is an old one. It is also one of the dreams of my youth, which have never left me …

We define predictive information I pred (T) as the mutual information between the past and
the future of a time series. Three qualitatively different behaviors are found in the limit of …

The p-factor is a construct that is thought to explain and maybe even cause variation in all
forms of psychopathology. Since its 'discovery'in 2012, hundreds of studies have been …

Much of perception, learning and high-level cognition involves finding patterns in data. But
there are always infinitely many patterns compatible with any finite amount of data. How …

The question of how one should decide among competing explanations of data is at the
heart of the scientific enterprise. Computational models of cognition are increasingly being …

We present an introduction to Bayesian inference as it is used in probabilistic models of
cognitive development. Our goal is to provide an intuitive and accessible guide to the what …