International Conference on Compute and Data Analysis

• Mathematical, probabilistic and statistical models and theories
  Machine learning theories, models and systems
  Knowledge discovery theories, models and systems
  Manifold and metric learning
  Deep learning
  Scalable analysis and learning
  Non-iidness learning
  Heterogeneous data/information integration
  Data pre-processing, sampling and reduction
  Dimensionality reduction
  Feature selection, transformation and construction
  Large scale optimization
  High performance computing for data analytics
  Architecture, management and process for data scienceLearning for streaming data
  Learning for structured and relational data
  Latent semantics and insight learning
  Mining multi-source and mixed-source information
  Mixed-type and structure data analytics
  Cross-media data analytics
  Big data visualization, modeling and analytics
  Multimedia/stream/text/visual analytics
  Relation, coupling, link and graph mining
  Personalization analytics and learning
  Web/online/social/network mining and learning
  Structure/group/community/network mining
  Cloud computing and service data analysis