Información de la conferencia
ICDMML 2019: International Conference on Data Mining and Machine Learning
http://www.icdmml.org/
Día de Entrega:
2018-12-30
Fecha de Notificación:
2019-01-15
Fecha de Conferencia:
2019-04-29
Ubicación:
Hong Kong, China
Vistas: 11140   Seguidores: 14   Asistentes: 1

Solicitud de Artículos
Artificial Intelligence

including the following topics but not limited to

    Artificial Intelligence
    Biometric Identification
    Biocomputing and Bioinformatics
    Computational Intelligence
    Cognitive Processing
    Computer Vision
    Deep learining
    Document Recognition and Understanding
    Humanoid Robot
    Intelligent Information Processing
    Intelligent Modeling and Control Theory
    Intelligent Vehicle
    Intelligent Video Surveillance
    Machine Learning
    Mass Information Processing
    Multimedia Information Processing
    Nature Language Processing
    Nonlinear System
    Pattern Recognition
    Quantum Computation and Quantum Information
    Space Robot
    Speech and Character Recognition
    Signal Processing
    Unmanned Aircraft
    Word Recognition

Data Mining

including the following topics but not limited to

    Abnormality and data detection
    Algorithms for new, structured, data types, such as arising in chemistry, biology, environment, and other scientific domains
    Big data analytic and High performance implementations of data mining algorithms
    Developing a unifying theory of data mining
    Distributed data mining and mining multi-agent data
    Mining high speed data streams
    Mining in networked settings: web, social and computer networks, and online communities
    Mining sequences and sequential data
    Mining sensor data
    Mining spatial and temporal datasets
    Mining textual and unstructured datasets
    Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis)

Machine Learning

including the following topics but not limited to

    Active learning
    Computational learning theory
    Distance measurement learning
    Deep learning
    Incremental learning and online learning
    Integrated learning
    Limit learning
    Machine learning new theory
    Manifold learning
    Multi - task learning
    Multi - sign learning
    Reinforcement learning
    Manifold learning
    Semi-supervised learning 
Última Actualización Por Dou Sun en 2018-05-09
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