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Bayesian interpretation of kernel regularization

Known as: Bayesian interpretation of regularization 
In machine learning, kernel methods arise from the assumption of an inner product space or similarity structure on inputs. For some such methods… Expand
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Papers overview

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2016
2016
Inspired by ideas taken from the machine learning literature, new regularization techniques have been recently introduced in… Expand
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2016
2016
All the approaches for hybrid system identification appeared in the literature assume that model complexity is known. Popular… Expand
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2015
2015
  • G. Pillonetto
  • IEEE 25th International Workshop on Machine…
  • 2015
  • Corpus ID: 11342271
All the approaches for identification of hybrid systems appeared in the literature assume known the model complexity. Widely used… Expand
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Highly Cited
2004
Highly Cited
2004
  • R. Szeliski
  • International Journal of Computer Vision
  • 2004
  • Corpus ID: 8433503
The need for error modeling, multisensor fusion, and robust algorithms is becoming increasingly recognized in computer vision… Expand
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2003
2003
Linear inverse problems with discrete data are equivalent to the estimation of the continuous-time input of a linear dynamical… Expand
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