Results 31 to 40 of about 9,484,631 (302)

Statistical Relational Learning [PDF]

, 2013
Relational learning refers to learning from data that have a complex structure. This structure may be either internal (a data instance may itself have a complex structure) or external (relationships between this instance and other data elements). Statistical relational learning refers to the use of statistical learning methods in a relational learning ...
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Preserved Statistical Learning of Tonal and Linguistic Material in Congenital Amusia [PDF]

, 2011
Congenital amusia is a lifelong disorder whereby individuals have pervasive difficulties in perceiving and producing music. In contrast, typical individuals display a sophisticated understanding of musical structure, even in the absence of musical ...
Stewart, Lauren, Lauren Stewart, Omigie, Diana, Stewart, L., Diana eOmigie, Lauren eStewart, Stewart, L; id_orcid, Diana Omigie, Omigie, D., Omigie, D   +9 more
core   +1 more source

The committee machine: Computational to statistical gaps in learning a two-layers neural network

, 2018
NeurIPS 2018 - Thirty-second Conference on Neural Information Processing Systems, Montreal, Canada, December 3-8ISBN: 9781510884472International audienceHeuristic tools from statistical physics have been used in the past to locate the phase transitions ...
Aubin, Benjamin, Maillard, Antoine, Barbier, Jean, Krzakala, Florent, Macris, Nicolas, Zdeborová, Lenka   +5 more
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Statistical Learning in High Energy and Astrophysics [PDF]

, 2005
This thesis studies the performance of statistical learning methods in high energy and astrophysics where they have become a standard tool in physics analysis.
Zimmermann, Jens
core   +1 more source

Unlocking stroke prediction: Harnessing projection-based statistical feature extraction with ML algorithms

Heliyon
Non-communicable diseases, such as cardiovascular disease, cancer, chronic respiratory diseases, and diabetes, are responsible for approximately 71% of all deaths worldwide.
Saad Sahriar, Sanjida Akther, Jannatul Mauya, Ruhul Amin, Md Shahajada Mia, Sabba Ruhi, Md Shamim Reza   +6 more
doaj   +1 more source

Optional Defaultable Markets

Risks, 2017
The paper deals with defaultable markets, one of the main research areas of mathematical finance. It proposes a new approach to the theory of such markets using techniques from the calculus of optional stochastic processes on unusual probability spaces ...
Mohamed N. Abdelghani, Alexander V. Melnikov   +1 more
doaj   +1 more source

Missing Risk Factor Prediction in Cardiovascular Disease Using a Blended Dataset and Optimizing Classification With a Stacking Algorithm

Engineering Reports
Machine learning is important in the treatment of heart disease because it is capable of analyzing large amounts of patient data, such as medical records, imaging tests, and genetic information, in order to identify patterns and predict the risk of ...
Jannatul Mauya, Saad Sahriar, Sanjida Akther, Ruhul Amin, Sabba Ruhi, Md. Shamim Reza   +5 more
doaj   +1 more source

AI-accelerated protein-ligand docking for SARS-CoV-2 is 100-fold faster with no significant change in detection

Scientific Reports, 2023
Protein-ligand docking is a computational method for identifying drug leads. The method is capable of narrowing a vast library of compounds down to a tractable size for downstream simulation or experimental testing and is widely used in drug discovery ...
Austin Clyde, Xuefeng Liu, Thomas Brettin, Hyunseung Yoo, Alexander Partin, Yadu Babuji, Ben Blaiszik, Jamaludin Mohd-Yusof, Andre Merzky, Matteo Turilli, Shantenu Jha, Arvind Ramanathan, Rick Stevens   +12 more
doaj   +1 more source

From statistical to causal learning

, 2023
To appear in the Proceedings of the International Congress of Mathematicians 2022, EMS Press. Both authors contributed equally to this work; names are listed in alphabetical order. 34 pages (28 content pages + references), 12 figures, 2 tables.
Bernhard Schölkopf, Julius von Kügelgen   +1 more
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On the Utility of E‐Learning in Statistics [PDF]

International Statistical Review, 2007
Summary Students of introductory courses consider statistics as particularly difficult, as the understanding of the underlying concepts may require more time and energy than for other disciplines. For decades statisticians have tried to enhance understanding with the help of technical solutions such as animation, video or interactive tools. However, it
Wolfgang Härdle, Sigbert Klinke, Uwe Ziegenhagen   +2 more
openaire   +2 more sources