Helsinki Institute for Information Technology

About: Helsinki Institute for Information Technology is a facility organization based out in Espoo, Finland. It is known for research contribution in the topics: Population & Bayesian network. The organization has 630 authors who have published 1962 publications receiving 63426 citations.

Exact Learning of Bounded Tree-width Bayesian Networks

Abstract: Inference in Bayesian networks is known to be NP-hard, but if the network has bounded treewidth, then inference becomes tractable. Not surprisingly, learning networks that closely match the given data and have a bounded tree-width has recently attracted some attention. In this paper we aim to lay groundwork for future research on the topic by studying the exact complexity of this problem. We give the first non-trivial exact algorithm for the NP-hard problem of finding an optimal Bayesian network of tree-width at most w, with running time 3 n n w+O(1) , and provide an implementation of this algorithm. Additionally, we propose a variant of Bayesian network learning with “super-structures”, and show that finding a Bayesian network consistent with a given super-structure is fixedparameter tractable in the tree-width of the super-structure.

A cognitive meta-analysis of design approaches to interruptions in intelligent environments

Abstract: Minimizing interruptions to users is a crucial and acknowledged precondition for the adoption of new intelligent technologies such as ubiquitous and proactive computing. This paper takes a step toward achieving a consensus among the numerous existing approaches addressing the challenge posed by interruptions. We start by explicating why interruptions are considered important. We then reveal similarities and differences among the approaches from a cognitive viewpoint. It appears that the approaches draw from different assumptions about human cognition. Some of the approaches contain inconsistencies. The cognitive analysis also inspires directions for future work.

The Boolean column and column-row matrix decompositions

Abstract: Matrix decompositions are used for many data mining purposes One of these purposes is to find a concise but interpretable representation of a given data matrix Different decomposition formulations have been proposed for this task, many of which assume a certain property of the input data (eg, nonnegativity) and aim at preserving that property in the decomposition In this paper we propose new decomposition formulations for binary matrices, namely the Boolean CX and CUR decompositions They are natural combinations of two previously presented decomposition formulations We consider also two subproblems of these decompositions and present a rigorous theoretical study of the subproblems We give algorithms for the decompositions and for the subproblems, and study their performance via extensive experimental evaluation We show that even simple algorithms can give accurate and intuitive decompositions of real data, thus demonstrating the power and usefulness of the proposed decompositions

There are 1,132,835,421,602,062,347 nonisomorphic one-factorizations of K14

Abstract: We establish by means of a computer search that a complete graph on 14 vertices has 98,758,655,816,833,727,741,338,583,040 distinct and 1,132,835,421,602,062,347 nonisomorphic one-factorizations The enumeration is constructive for the 10,305,262,573 isomorphism classes that admit a nontrivial automorphism © 2008 Wiley Periodicals, Inc J Combin Designs 17: 147–159, 2009

Dynamics and impact of homologous recombination on the evolution of Legionella pneumophila.

Abstract: Legionella pneumophila is an environmental bacterium and the causative agent of Legionnaires' disease. Previous genomic studies have shown that recombination accounts for a high proportion (>96%) of diversity within several major disease-associated sequence types (STs) of L. pneumophila. This suggests that recombination represents a potentially important force shaping adaptation and virulence. Despite this, little is known about the biological effects of recombination in L. pneumophila, particularly with regards to homologous recombination (whereby genes are replaced with alternative allelic variants). Using newly available population genomic data, we have disentangled events arising from homologous and non-homologous recombination in six major disease-associated STs of L. pneumophila (subsp. pneumophila), and subsequently performed a detailed characterisation of the dynamics and impact of homologous recombination. We identified genomic "hotspots" of homologous recombination that include regions containing outer membrane proteins, the lipopolysaccharide (LPS) region and Dot/Icm effectors, which provide interesting clues to the selection pressures faced by L. pneumophila. Inference of the origin of the recombined regions showed that isolates have most frequently imported DNA from isolates belonging to their own clade, but also occasionally from other major clades of the same subspecies. This supports the hypothesis that the possibility for horizontal exchange of new adaptations between major clades of the subspecies may have been a critical factor in the recent emergence of several clinically important STs from diverse genomic backgrounds. However, acquisition of recombined regions from another subspecies, L. pneumophila subsp. fraseri, was rarely observed, suggesting the existence of a recombination barrier and/or the possibility of ongoing speciation between the two subspecies. Finally, we suggest that multi-fragment recombination may occur in L. pneumophila, whereby multiple non-contiguous segments that originate from the same molecule of donor DNA are imported into a recipient genome during a single episode of recombination.