Results 51 to 60 of about 1,606,312 (290)
An incremental approach to genetic algorithms based classification [PDF]
, 2005 Incremental learning has been widely addressed in the machine learning literature to cope with learning tasks where the learning environment is ever changing or training samples become available over time. However, most research work explores incremental
Guan, SU, Zhu, F
core +3 more sources
Molecular Oncology, EarlyView.Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova +25 more
wiley +1 more source
Quest for Compounds at the Verge of Charge Transfer Instabilities: The Case of Silver(II) Chloride †
Crystals, 2019 Electron-transfer processes constitute one important limiting factor governing stability of solids. One classical case is that of CuI2, which has never been prepared at ambient pressure conditions due to feasibility of charge transfer between metal and ...
Mariana Derzsi +4 more
doaj +1 more source
Coherent control using adaptive learning algorithms
, 2001 We have constructed an automated learning apparatus to control quantum systems. By directing intense shaped ultrafast laser pulses into a variety of samples and using a measurement of the system as a feedback signal, we are able to reshape the laser ...
A. Assion +32 more
core +1 more source
FEBS Open Bio, EarlyView.In this study, we developed a deep learning method for mitotic figure counting in H&E‐stained whole‐slide images and evaluated its prognostic impact in 13 external validation cohorts from seven different cancer types. Patients with more mitotic figures per mm2 had significantly worse patient outcome in all the studied cancer types except colorectal ...
Joakim Kalsnes +32 more
wiley +1 more source
Efficient learning in ABC algorithms [PDF]
, 2012 Approximate Bayesian Computation has been successfully used in population genetics to bypass the calculation of the likelihood. These methods provide accurate estimates of the posterior distribution by comparing the observed dataset to a sample of ...
Cornuet, Jean-Marie +4 more
core +2 more sources
Stability of Unstable Learning Algorithms [PDF]
Machine Learning, 2007 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Don R. Hush +2 more
openaire +2 more sources
Digital twins to accelerate target identification and drug development for immune‐mediated disorders
FEBS Open Bio, EarlyView.Digital twins integrate patient‐derived molecular and clinical data into personalised computational models that simulate disease mechanisms. They enable rapid identification and validation of therapeutic targets, prediction of drug responses, and prioritisation of candidate interventions.
Anna Niarakis, Philippe Moingeon
wiley +1 more source
Investigation of Q-Learning in the Context of a Virtual Learning Environment
Informatics in Education, 2007 We investigate the possibility to apply a known machine learning algorithm of Q-learning in the domain of a Virtual Learning Environment (VLE). It is important in this problem domain to have algorithms that learn their optimal values in a rather short ...
Dalia BAZIUKAITE
doaj +1 more source
Energy Science & Engineering, 2022 Buildings are one of the largest consumers of electrical energy, making it important to develop different strategies to help to reduce electricity consumption.
D. Mariano‐Hernández +8 more
doaj +1 more source