Author | Conference | Journal | Organization | Year | DOI
Look for results that meet for the following criteria:
Academic
Keywords
Machine Learning

ML,Machine Learning,machine learn,machine learned,machines learning,machines learn,machine learns,machinely learned

Machine Learning - ML
Publications: 32,119| Citation Count: 340,104
Stemming Variations: machine learn, machine learned, machines learning, machines learn, machine learns
Cumulative Annual
    • Machine learning (ML) is a complex process that can hardly be carried out by non-expert users. Especially when using adaptive systems that interpret and exploit observations of the user to modify their behavior according to the user's perceived preferences, even naïve users may be confronted with learning systems...

    Mathias Bauer, et al. An ontology-based interface for machine learning

    • Machine Learning is an important area of Artificial Intelligence which is generally applicable to almost any field of science. Early exposure of students to the potential of machine learning could have a positive impact on their attitude towards Artificial Intelligence in particular and computer science in general...

    Vasile Rus, et al. MLeXAI: BIOMEDICAL TERM CLASSIFICATION

    • Machine Learning is a computational methodology that provides automatic means of improving programmed tasks from experience. As a subfield of Machine Learning, Grammatical Inference (GI) attempts to learn structural models, such as grammars, from diverse data patterns, such as speech, artificial and natural languages, sequences provided by bioinformatics databases, amongst others...

    ABOUBEKEUR HAMDI-CHERIF, et al. Grammatical Inference Methodology for Control Systems

    • Machine learning is an important part of artificial intelligence and its applications. Learningfrom instances is one of the most active areas within machine learning. Initial successesin the induction of propositional theories have been followed by algorithms that constructhypotheses in the form of (a subset of) the first order relational concepts. Such learning iscalled Inductive Logic Programming (ILP).This thesis deals with two key problems of machine learning of concepts from...

    Matevz Kovacic. Stochastic Inductive Logic Programming

    • Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to "learn" from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction...

    Joseph A. Cruz, et al. Applications of Machine Learning in Cancer Prediction and Prognosis

Sort by:

Publications (32119)

Share this on