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Institution

Helsinki Institute for Information Technology

FacilityEspoo, Finland
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.


Papers
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Journal Article
TL;DR: In this article, the authors discuss the collection of personal information in the cloud and the legitimate exploitation of it by third parties, and propose a solution to the problem of privacy protection in the Cloud.
Abstract: Cloud computing can be defined as the provision of computing resources on-demand over the Internet. Although this might bring a number of advantages to end-users in terms of accessibility and elasticity of costs, problems arise concerning the collection of personal information in the Cloud and the legitimate exploitation thereof. To the extent that most of the content and software application are only accessible online, users have no longer control over the manner in which they can access their data and the extent to which third parties can exploit it.

28 citations

Journal ArticleDOI
24 Mar 2014
TL;DR: This contribution provides a breakdown of the steps necessary for using a digital game in experimental studies, along with a checklist for researchers illustrating variables that potentially affect the reliability and validity of experiments.
Abstract: Digital games offer rich media content and engaging action, accessible individually or in groups collaborating or competing against each other. This makes them promising for use as a stimulus in research settings. This paper examines the advantages and challenges of using games in experimental research with particular focus on strict stimulus control through the following four areas: (1) matching and regulating task type, (2) data segmentation and event coding, (3) compatibility between participants, and (4) planning and conducting data collection. This contribution provides a breakdown of the steps necessary for using a digital game in experimental studies, along with a checklist for researchers illustrating variables that potentially affect the reliability and validity of experiments. We also offer a study example to illustrate how these considerations apply to practice. The aim is to provide support to researchers planning and conducting empirical experiments involving games, and also to those evaluating the works of others.

28 citations

Posted ContentDOI
29 Oct 2019-bioRxiv
TL;DR: In vivo MOR availability in the brains of 204 individuals with no neurologic or psychiatric disorders is quantified using positron emission tomography (PET) with tracer [11C]carfentanil and Bayesian hierarchical modeling to estimate the effects of sex, age, body mass index (BMI) and smoking on [11Cs)carfENTanil binding potential.
Abstract: The brain9s mu-opioid receptors (MORs) are involved in analgesia, reward and mood regulation. Several neuropsychiatric diseases have been associated with dysfunctional MOR system, and there is also considerable variation in receptor density among healthy individuals. Sex, age, body mass and smoking have been proposed to influence the MOR system, but due to small sample sizes the magnitude of their influence remains inconclusive. Here we quantified in vivo MOR availability in the brains of 204 individuals with no neurologic or psychiatric disorders using positron emission tomography (PET) with tracer [11C]carfentanil. We then used Bayesian hierarchical modeling to estimate the effects of sex, age, body mass index (BMI) and smoking on [11C]carfentanil binding potential. We also examined hemispheric lateralization of MOR availability. Age had regionally specific effects on MOR availability, with age-dependent increase in frontotemporal areas but decrease in amygdala, thalamus, and nucleus accumbens. The age-dependent increase was stronger in males. MOR availability was globally lowered in smokers but independent of BMI. Finally, MOR availability was higher in the right versus the left hemisphere. The presently observed variation in MOR availability may explain why some individuals are prone to develop MOR-linked pathological states, such as chronic pain or psychiatric disorders.

28 citations

Posted Content
TL;DR: In this paper, the authors combine the two approaches by presenting a novel HDP-based topic model that automatically learns both shared and private topics, which is shown to be especially useful for querying the contents of one domain given samples of the other.
Abstract: Multi-modal data collections, such as corpora of paired images and text snippets, require analysis methods beyond single-view component and topic models. For continuous observations the current dominant approach is based on extensions of canonical correlation analysis, factorizing the variation into components shared by the different modalities and those private to each of them. For count data, multiple variants of topic models attempting to tie the modalities together have been presented. All of these, however, lack the ability to learn components private to one modality, and consequently will try to force dependencies even between minimally correlating modalities. In this work we combine the two approaches by presenting a novel HDP-based topic model that automatically learns both shared and private topics. The model is shown to be especially useful for querying the contents of one domain given samples of the other.

28 citations

Journal ArticleDOI
TL;DR: It is shown that a simple randomized algorithm has an expected constant factor approximation guarantee for fitting bucket orders to a set of pairwise preferences.

28 citations


Authors

Showing all 632 results

NameH-indexPapersCitations
Dimitri P. Bertsekas9433285939
Olli Kallioniemi9035342021
Heikki Mannila7229526500
Jukka Corander6641117220
Jaakko Kangasjärvi6214617096
Aapo Hyvärinen6130144146
Samuel Kaski5852214180
Nadarajah Asokan5832711947
Aristides Gionis5829219300
Hannu Toivonen5619219316
Nicola Zamboni5312811397
Jorma Rissanen5215122720
Tero Aittokallio522718689
Juha Veijola5226119588
Juho Hamari5117616631
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20231
20224
202185
202097
2019140
2018127