Results 61 to 70 of about 137,057 (303)
Directed evolution of enzymes at the crossroads of tradition and innovation
FEBS Open Bio, EarlyView.An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova +2 more
wiley +1 more source
A Survey of Constrained Clustering [PDF]
, 2016 This book summarizes the state-of-the-art in unsupervised learning. The contributors discuss how with the proliferation of massive amounts of unlabeled data, unsupervised learning algorithms, which can automatically discover interesting and useful ...
Tural, Mustafa Kemal +3 more
core +1 more source
Incremental ELMVIS for Unsupervised Learning [PDF]
, 2017 An incremental version of the ELMVIS+ method is proposed in this paper. It iteratively selects a few best fitting data samples from a large pool, and adds them to the model. The method keeps high speed of ELMVIS+ while allowing for much larger possible sample pools due to lower memory requirements.
Anton Akusok +7 more
openaire +2 more sources
Digital Cognitive Phenotyping for Differential Diagnosis and Monitoring in Neurological Conditions
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To assess the utility, accessibility, and equivalence to supervised scales of online cognitive assessment in older individuals with cognitive impairment. Methods Patients with Alzheimer's disease (AD, n = 31), idiopathic normal pressure hydrocephalus (iNPH, n = 26), and traumatic brain injury (TBI, n = 23) completed online cognitive ...
Martina Del Giovane +10 more
wiley +1 more source
Arthritis Care &Research, EarlyView.Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos +2 more
wiley +1 more source
Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
Evaluating unsupervised fault detection in self-healing systems using stochastic primitives [PDF]
, 2015 This research was partially supported by the Scottish Informatics and Computer Science Alliance (SICSA).Autonomous fault detection represents one approach for reducing operational costs in large-scale computing environments.
Barker, Adam David +5 more
core +1 more source
An Unsupervised Learning Approach to Condition Assessment on a Wound-Rotor Induction Generator
Energies, 2021 Accurate online diagnosis of incipient faults and condition assessment on generators is especially challenging to automate through supervised learning techniques, because of data imbalance.
Elsie Swana, Wesley Doorsamy
doaj +1 more source
PASTA‐ELN: Simplifying Research Data Management for Experimental Materials Science
Advanced Engineering Materials, EarlyView.Research data management faces ongoing hurdles as many ELNs remain complex and restrictive. PASTA‐ELN offers an open‐source, cross‐platform solution that prioritizes simplicity, offline access, and user control. Its in tuitive folder structure, modular Python add‐ons, and open formats enable seamless documentation, FAIR data practices, and easy ...
S. Brinckmann, G. Winkens, R. Schwaiger
wiley +1 more source
Unsupervised learning by program synthesis [PDF]
, 2015 We introduce an unsupervised learning algorithmthat combines probabilistic modeling with solver-based techniques for program synthesis.We apply our techniques to both a visual learning domain and a language learning problem,showing that our algorithm can
Tenenbaum, Joshua B +2 more
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