Zobrazeno 1 - 10
of 59
pro vyhledávání: '"Petri Myllymäki"'
Autor:
Giulio Jacucci, Manuel J. A. Eugster, Petri Myllymäki, Patrik Floréen, Jaakko Peltonen, Samuel Kaski, Dorota Glowacka, Tuukka Ruotsalo
Publikováno v:
ACM TRANSACTIONS ON INFORMATION SYSTEMS. 36(4):1-46
Exploratory search requires the system to assist the user in comprehending the information space and expressing evolving search intents for iterative exploration and retrieval of information. We introduce interactive intent modeling, a technique that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9e7eddd221d9fdc04cdfcdd6a3f5e5b6
http://juuli.fi/Record/0334285418
http://juuli.fi/Record/0334285418
Publikováno v:
Machine Learning. 107:247-283
Various algorithms have been proposed for finding a Bayesian network structure that is guaranteed to maximize a given scoring function. Implementations of state-of-the-art algorithms, solvers, for this Bayesian network structure learning problem rely
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ede9b38957d675d624a46df17fd5273
https://doi.org/10.1007/s10994-017-5680-2
https://doi.org/10.1007/s10994-017-5680-2
Publikováno v:
MLSP
High power ultrasound permits non-invasive cleaning of industrial equipment, but to make such cleaning systems energy efficient, one needs to recognize when the structure has been sufficiently cleaned without using invasive diagnostic tools. This can
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::904e018962f765845370df85689188a9
https://doi.org/10.1109/mlsp.2018.8517080
https://doi.org/10.1109/mlsp.2018.8517080
Publikováno v:
New Generation Computing. 35:47-67
We address the well-known score-based Bayesian network structure learning problem. Breadth-first branch and bound (BFBnB) has been shown to be an effective approach for solving this problem. Duplicate detection is an important component of the BFBnB
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3f569e93ba3148dab8f476f13ba9ebd6
https://doi.org/10.1007/s00354-016-0004-9
https://doi.org/10.1007/s00354-016-0004-9
Publikováno v:
COMMUNICATIONS OF THE ACM. 58(1):86-92
The system should let users incrementally direct their search toward relevant, though not initially obvious, information.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b065c839160eb2e0feb6906d23f3d148
http://juuli.fi/Record/0337688515
http://juuli.fi/Record/0337688515
Publikováno v:
University of Helsinki
Finding the location of a robot, equipped with an imaging sensor, by taking photos from its surrounding environment is a multifaceted task consisting several obligatory phases. It starts from the calibration of a sensor, and ends in propagation of er
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::56c46b9c974afca85727ecc8bfb68376
https://doi.org/10.4018/ijrat.2014070102
https://doi.org/10.4018/ijrat.2014070102
Publikováno v:
International Journal of Approximate Reasoning. 51(5):544-557
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background knowledge is available. The problem can be divided into two different sub
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::03957cf6f87045629c4dca8fbbb592e5
Publikováno v:
Journal of Multivariate Analysis. 101(4):839-849
Model selection by means of the predictive least squares (PLS) principle has been thoroughly studied in the context of regression model selection and autoregressive (AR) model order estimation. We introduce a new criterion based on sequentially minim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad41bf21c466171112523c6c24fc849a
Autor:
Petri Kontkanen, Petri Myllymäki
Publikováno v:
Information Processing Letters. 103:227-233
The minimum description length (MDL) principle is a theoretically well-founded, general framework for performing model class selection and other types of statistical inference. This framework can be applied for tasks such as data clustering, density
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e642c3ed0ff645487229b9befab2dd5f
https://doi.org/10.1016/j.ipl.2007.04.003
https://doi.org/10.1016/j.ipl.2007.04.003
Publikováno v:
BMC Bioinformatics
Background Statistical modeling of transcription factor binding sites is one of the classical fields in bioinformatics. The position weight matrix (PWM) model, which assumes statistical independence among all nucleotides in a binding site, used to be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6bc2deb8af577be083c1152a4f1ef892
https://doi.org/10.1186/s12859-015-0797-4
https://doi.org/10.1186/s12859-015-0797-4