Results 31 to 40 of about 726,930 (286)
Escaping Local Optima in a Class of Multi-Agent Distributed Optimization Problems: A Boosting Function Approach [PDF]
, 2014 We address the problem of multiple local optima commonly arising in optimization problems for multi-agent systems, where objective functions are nonlinear and nonconvex.
Cassandras, Christos G. +2 more
core +2 more sources
Foundations and Innovations in Data Fusion and Ensemble Learning for Effective Consensus
MathematicsEnsemble learning and data fusion techniques play a crucial role in modern machine learning, enhancing predictive performance, robustness, and generalization.
Ke-Lin Du +4 more
doaj +1 more source
Boosting for high-dimensional linear models
, 2006 We prove that boosting with the squared error loss, $L_2$Boosting, is consistent for very high-dimensional linear models, where the number of predictor variables is allowed to grow essentially as fast as $O$(exp(sample size)), assuming that the true ...
Bühlmann, Peter
core +2 more sources
PREDICTION OF SOFTWARE ANOMALIES METHODS BASED ON ENSEMBLE LEARNING METHODS
Mağallaẗ Al-kūfaẗ Al-handasiyyaẗSoftware plays a vital role in all aspects of our daily lives, specifically in the fields of medicine and industry. In order to design high-quality and reliable software and avoid risks resulting from software errors, including physical and human errors,
Raghda Azad Hasan, Ibrahim Ahmed Saleh
doaj +1 more source
FEBS Letters, EarlyView.Plasma membranes contain dynamic nanoscale domains that organize lipids and receptors. Because viruses operate at similar scales, this architecture shapes early infection steps, including attachment, receptor engagement, and entry. Using influenza A virus and HIV‐1 as examples, we highlight how receptor nanoclusters, multivalent glycan interactions ...
Jan Schlegel, Christian Sieben
wiley +1 more source
Molecular Oncology, EarlyView.Meta‐transcriptome analysis identified FGF19 as a peptide enteroendocrine hormone associated with colorectal cancer prognosis. In vivo xenograft models showed release of FGF19 into the blood at levels that correlated with tumor volumes. Tumoral‐FGF19 altered murine liver metabolism through FGFR4, thereby reducing bile acid synthesis and increasing ...
Jordan M. Beardsley +5 more
wiley +1 more source
An update on statistical boosting in biomedicine [PDF]
, 2017 Statistical boosting algorithms have triggered a lot of research during the last decade. They combine a powerful machine-learning approach with classical statistical modelling, offering various practical advantages like automated variable selection and ...
Gefeller, Olaf +5 more
core +4 more sources
Advances in Physics: X, 2019 Technological advancements enable collecting vast data, i.e., Big Data, in science and industry including biomedical field. Increased computational power allows expedient analysis of collected data using statistical and machine-learning approaches ...
Valeriy Gavrishchaka +2 more
doaj +1 more source
Frontiers in Public Health, 2020 A considerable amount of health record (HR) data has been stored due to recent advances in the digitalization of medical systems. However, it is not always easy to analyze HR data, particularly when the number of persons with a target disease is too ...
Koichi Fujiwara +6 more
doaj +1 more source
Development and Evaluation of Ensemble Learning Models for Detection of DDOS Attacks in IoT
Hittite Journal of Science and Engineering, 2022 Internet of Things that process tremendous confidential data have difficulty performing traditional security algorithms, thus their security is at risk.
Selim Buyrukoğlu, Yıldıran Yılmaz
doaj +1 more source