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Learning functional dependencies with kernel methods




In this paper, we review some recent research directions regarding the synthesis of functions from data using kernel methods. We start by highlighting the central role of the representer theorem and then outline some recent advances in large scale optimization, learning the kernel, and multi-task learning.

Author(s): Dinuzzo, F.
Journal: Scientifica Acta
Volume: 4
Number (issue): 1
Pages: 16-25
Year: 2010
Day: 0

Department(s): Empirical Inference
Bibtex Type: Article (article)

Links: Web


  title = {Learning functional dependencies with kernel methods},
  author = {Dinuzzo, F.},
  journal = {Scientifica Acta},
  volume = {4},
  number = {1},
  pages = {16-25},
  year = {2010}