Corpus ID: 125481946

Operator Theory for Analysis of Convex Optimization Methods in Machine Learning

@inproceedings{Gallagher2014OperatorTF,
  title={Operator Theory for Analysis of Convex Optimization Methods in Machine Learning},
  author={P. W. Gallagher},
  year={2014}
}
  • P. W. Gallagher
  • Published 2014
  • Mathematics
  • Author(s): Gallagher, Patrick W. | Abstract: As machine learning has more closely interacted with optimization, the concept of convexity has loomed large. Two properties beyond simple convexity have received particularly close attention: strong smoothness and strong convexity. These properties (and their relatives) underlie machine learning analyses from convergence rates to generalization bounds --- they are central and fundamental. This thesis takes as its focus properties from operator… CONTINUE READING