Primal-Dual Rates and Certificates

  title={Primal-Dual Rates and Certificates},
  author={Celestine D{\"u}nner and Simone Forte and Martin Tak{\'a}c and Martin Jaggi},
We propose an algorithm-independent framework to equip existing optimization methods with primal-dual certificates. Such certificates and corresponding rate of convergence guarantees are important for practitioners to diagnose progress, in particular in machine learning applications. We obtain new primal-dual convergence rates, e.g., for the Lasso as well as many L1, Elastic Net, group Lasso and TV-regularized problems. The theory applies to any norm-regularized generalized linear model. Our… CONTINUE READING
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Adaptive PrimalDual Splitting Methods for Statistical Learning and Image Processing

  • Goldstein, Tom, Li, Min, Yuan, Xiaoming
  • In NIPS 2015 - Advances in Neural Information…
  • 2015
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