Zobrazeno 1 - 10
of 72
pro vyhledávání: '"Teemu Roos"'
Autor:
Eira Roos, Sanna Heikkinen, Karri Seppä, Olli Pietiläinen, Heidi Ryynänen, Maarit Laaksonen, Teemu Roos, Paul Knekt, Satu Männistö, Tommi Härkänen, Pekka Jousilahti, Seppo Koskinen, Johan G. Eriksson, Nea Malila, Ossi Rahkonen, Janne Pitkäniemi
Publikováno v:
Preventive Medicine Reports, Vol 38, Iss , Pp 102607- (2024)
Smoking, alcohol consumption, obesity, and physical inactivity are key lifestyle risk factors for cancer. Previously these have been mostly examined singly or combined as an index, assuming independent and equivalent effects to cancer risk. The aim o
Externí odkaz:
https://doaj.org/article/79de86af9d204eaa9a13559842592fe4
Autor:
Eira Roos, Karri Seppä, Olli Pietiläinen, Heidi Ryynänen, Sanna Heikkinen, Johan G. Eriksson, Tommi Härkänen, Pekka Jousilahti, Paul Knekt, Seppo Koskinen, Maarit Laaksonen, Satu Männistö, Teemu Roos, Ossi Rahkonen, Nea Malila, Janne Pitkäniemi, The METCA Study Group
Publikováno v:
Cancer Reports, Vol 5, Iss 11, Pp n/a-n/a (2022)
Abstract Background Several lifestyle factors are associated with an increased risk of colorectal cancer (CRC). Although lifestyle factors co‐occur, in most previous studies these factors have been studied focusing upon a single risk factor or assu
Externí odkaz:
https://doaj.org/article/04bf0c8ca6a34836814af39c92cc412d
Autor:
Peter Grünwald, Teemu Roos
Publikováno v:
International Journal of Mathematics for Industry, Vol 11, Iss 1, Pp 1930001-1-1930001-29 (2019)
This is an up-to-date introduction to and overview of the Minimum Description Length (MDL) Principle, a theory of inductive inference that can be applied to general problems in statistics, machine learning and pattern recognition. While MDL was origi
Externí odkaz:
https://doaj.org/article/a32c270bc57e4e659eb8b5bb58564eba
Autor:
Jussi Määttä, Teemu Roos
Publikováno v:
PLoS ONE, Vol 11, Iss 4, p e0152656 (2016)
The maximum parsimony (MP) method for inferring phylogenies is widely used, but little is known about its limitations in non-asymptotic situations. This study employs large-scale computations with simulated phylogenetic data to estimate the probabili
Externí odkaz:
https://doaj.org/article/e12d00af615045c28abf521efe19b8cc
Many applications, especially in physics and other sciences, call for easily interpretable and robust machine learning techniques. We propose a fully gradient-based technique for training radial basis function networks with an efficient and scalable
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd616e8f011915cf58267af1f1606584
http://hdl.handle.net/10138/324975
http://hdl.handle.net/10138/324975
Autor:
Tuomas Heikkilä, Teemu Roos
Publikováno v:
Digital Scholarship in the Humanities. 33:766-787
The article explores the uses of quantitative approaches used in textual scholarship in studying large amounts of medieval hand-written calendars. Calendars are exceedingly numerous among medieval manuscript sources but have been studied surprisingly
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d8ecefb3cd2204dfe7eadf2918856f98
https://doi.org/10.1093/llc/fqy007
https://doi.org/10.1093/llc/fqy007
Autor:
Teemu Roos, Fredrik Heintz
Publikováno v:
EDULEARN Proceedings.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2834a067824dc231ae64d82982a74de7
https://doi.org/10.21125/edulearn.2021.0559
https://doi.org/10.21125/edulearn.2021.0559
Autor:
Aqsa Saeed Qureshi, Teemu Roos
Early diagnosis plays a key role in prevention and treatment of skin cancer. Several machine learning techniques for accurate detection of skin cancer from medical images have been reported. Many of these techniques are based on pre-trained convoluti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a4615f6d5715b1aaecad47b6a5a0ff3
Publikováno v:
Advances in Knowledge Discovery and Data Mining ISBN: 9783030161446
PAKDD (2)
PAKDD (2)
Approximate nearest neighbor algorithms are used to speed up nearest neighbor search in a wide array of applications. However, current indexing methods feature several hyperparameters that need to be tuned to reach an acceptable accuracy--speed trade
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3b20bfe7e040c8b7866fe263be661fe6
https://doi.org/10.1007/978-3-030-16145-3_46
https://doi.org/10.1007/978-3-030-16145-3_46
We introduce an approach to divisive hierarchical clustering that is capable of identifying clusters in nonlinear manifolds. This approach uses the isometric mapping (Isomap) to recursively embed (subsets of) the data in one dimension, and then perfo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b3854c6b307309de3bd5d44a8262c82a
https://doi.org/10.1016/j.patcog.2020.107508
https://doi.org/10.1016/j.patcog.2020.107508