On Friday the 24th of January 2020, M.Sc. Janne Leppä-aho will defend his doctoral thesis on Methods for Learning Directed and Undirected Graphical Models. The thesis is a part of research done in the ...

Graphical models form a cornerstone of modern data analysis by providing a visually intuitive framework to represent and reason about the complex interdependencies among variables. In particular, ...

Probabilistic graphical models are a powerful technique for handling uncertainty in machine learning. The course will cover how probability distributions can be represented in graphical models, how ...

This paper consists of a collection of (mostly) pen-and-paper exercises in machine learning. The exercises are on the following topics: linear algebra, optimization, directed graphical models, ...

It has been estimated that about 30% of the genes in the human genome are regulated by microRNAs (miRNAs). These are short RNA sequences that can down-regulate the levels of mRNAs or proteins in ...

This is a preview. Log in through your library . Abstract We review recent developments in applying Bayesian probabilistic and statistical ideas to expert systems. Using a real, moderately complex, ...