Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Sakira Hassan"'
Autor:
Syeda Sakira Hassan, Simo Sarkka
Publikováno v:
IEEE Transactions on Automatic Control. :1-8
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1dd429d3419162e6d1f7e8d17a5e0ae1
https://doi.org/10.1109/tac.2023.3234236
https://doi.org/10.1109/tac.2023.3234236
Publikováno v:
Cancer Informatics, Vol 2015, Iss Suppl. 5, Pp 75-85 (2016)
Externí odkaz:
https://doaj.org/article/9a6f8c9b26f44036ade9d6d9b6610f17
Publikováno v:
Image Analysis ISBN: 9783031314377
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c18f404df2a9d94abdc21f3f31273803
https://doi.org/10.1007/978-3-031-31438-4_25
https://doi.org/10.1007/978-3-031-31438-4_25
Publikováno v:
Cancer Informatics, Vol 14s5 (2015)
In this paper, we study the problem of feature selection in cancer-related machine learning tasks. In particular, we study the accuracy and stability of different feature selection approaches within simplistic machine learning pipelines. Earlier stud
Externí odkaz:
https://doaj.org/article/fcf1270859fb4224ac0b03be6b7159ff
Publikováno v:
IEEE Transactions on Signal Processing
This paper presents algorithms for parallelization of inference in hidden Markov models (HMMs). In particular, we propose parallel backward-forward type of filtering and smoothing algorithm as well as parallel Viterbi-type maximum-a-posteriori (MAP)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ce8f9c8af6e01f42a94899001e8910f8
http://arxiv.org/abs/2102.05743
http://arxiv.org/abs/2102.05743
Publikováno v:
ICASSP
The problem of Bayesian filtering and smoothing in nonlinear models with additive noise is an active area of research. Classical Taylor series as well as more recent sigma-point based methods are two well-known strategies to deal with these problems.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1b236f66a386d5ef5d0bd1525601e3d5
We propose a novel classifier accuracy metric: the Bayesian Area Under the Receiver Operating Characteristic Curve (CBAUC). The method estimates the area under the ROC curve and is related to the recently proposed Bayesian Error Estimator. The metric
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::45e8b707065149aefc067268bffa8fe8
Autor:
Syeda Sakira Hassan
Publikováno v:
Tampere University
Over recent years, data-intensive science has been playing an increasingly essential role in biological discovery and biomedical science. The explosion of information in biology poses challenges in organizing data, discovering relevant information fr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::40e909e1f289b15529490056d6b34f0e
Identification of feasible pathway information for c-di-GMP binding proteins in cellulose production
Publikováno v:
IFMBE Proceedings ISBN: 9789811051210
In this paper, we utilize a machine learning approach to identify the significant pathways for c-di-GMP signaling proteins. The dataset involves gene counts from 12 pathways and 5 essential c-di-GMP binding domains for 1024 bacterial genomes. Two nov
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::35b2ab3473611b05aa5ac693722ee187
https://doi.org/10.1007/978-981-10-5122-7_167
https://doi.org/10.1007/978-981-10-5122-7_167
Publikováno v:
Cancer Informatics, Vol 14s5 (2015)
Cancer Informatics
Cancer Informatics, Vol 2015, Iss Suppl. 5, Pp 75-85 (2016)
Cancer Informatics
Cancer Informatics, Vol 2015, Iss Suppl. 5, Pp 75-85 (2016)
In this paper, we study the problem of feature selection in cancer-related machine learning tasks. In particular, we study the accuracy and stability of different feature selection approaches within simplistic machine learning pipelines. Earlier stud
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60fe8ce8be7836003d5fcad705b57656
https://trepo.tuni.fi/handle/10024/99726
https://trepo.tuni.fi/handle/10024/99726