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Statistics Gathering for Learning from Distributed, Heterogeneous and Autonomous Data Sources.

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Incremental and Distributed Learning with Support Vector Machines., , and . AAAI/IAAI, page 1067. AAAI Press / The MIT Press, (2000)Multinomial Event Model Based Abstraction for Sequence and Text Classification., , , and . SARA, volume 3607 of Lecture Notes in Computer Science, page 134-148. Springer, (2005)Identifying Informative Messages in Disasters using Convolutional Neural Networks., , and . ISCRAM, ISCRAM Association, (2016)Classifying Scientific Publications Using Abstract Features., , , , and . SARA, AAAI, (2011)Information Integration and Knowledge Acquisition from Semantically Heterogeneous Biological Data Sources., , , , , , and . DILS, volume 3615 of Lecture Notes in Computer Science, page 175-190. Springer, (2005)Abstraction Super-Structuring Normal Forms: Towards a Theory of Structural Induction., and . Algorithmic Probability and Friends, volume 7070 of Lecture Notes in Computer Science, page 339-350. Springer, (2011)Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources., , and . Emergent Neural Computational Architectures Based on Neuroscience, volume 2036 of Lecture Notes in Computer Science, page 547-559. Springer, (2001)Learning Decision Trees form Distributed Heterogeneous Autonomous Data., , and . MAICS, page 10-17. Omnipress, (2003)Protein Sequence Classification Using Feature Hashing., , and . BIBM, page 538-543. IEEE Computer Society, (2011)Abstraction Augmented Markov Models., , , and . ICDM, page 68-77. IEEE Computer Society, (2010)