@InProceedings{Uricar-Franc-CVWW-2012,
  IS = { zkontrolovano 14 Jan 2013 },
  UPDATE  = { 2012-03-02 },
  author =      {U{\v{r}}i{\v{c}}{\'{a}}{\v{r}}, Michal and Franc, Vojt{\v{e}}ch },
  language =    {English},
  title =       {Efficient Algorithm for Regularized Risk Minimization},
  c_title =     {Efektivn{\' i} Algoritmus pro minimalizaci regularizovan{\' e}ho risku},
  year =        {2012},
  pages =       {57-64},
  booktitle =   {CVWW '12: Proceedings of the 17th Computer Vision Winter Workshop},
  editor =      {Kristan, Matej and Mandeljc, Rok and {\v C}echovin, Luka},
  publisher =   {Slovenian Pattern Recognition Society},
  address =     {Ljubljana, Slovenia},
  isbn =        {978-961-90901-6-9},
  book_pages =  {181},
  month =       {February},
  day =         {1-3},
  venue =       {Mala Nedelja, Slovenia},
  annote =      {Many machine learning algorithms lead to solving a
    convex regularized risk minimization problem. Despite its
    convexity the problem is often very demanding in practice due to a
    high number of variables or a complex objective function. The
    Bundle Method for Risk Minimization (BMRM) is a recently proposed
    method for minimizing a generic regularized risk. Unlike the
    approximative methods, the BMRM algorithm comes with convergence
    guarantees but it is often too slow in practice. We propose a
    modified variant of the BMRM algorithm which decomposes the
    objective function into several parts and approximates each part
    by a separate cutting plane model instead of a single cutting
    plane model used in the original BMRM. The finer approximation of
    the objective function can significantly decrease the number of
    iterations at the expense of higher memory requirements. A
    preliminary experimental comparison shows promising results.},
  keywords =    {Machine Learning, Regularized Risk Minimization, Cutting planes},
  prestige =    {international},
  authorship =  {50-50},
  project =     {FP7-ICT-247525 HUMAVIPS, PERG04-GA-2008-239455 SEMISOL},
  psurl = {[UricarFranc-CVWW2012.pdf]},
  www = {http://cvww2012.vicos.si/},
  acceptance_ratio = {0.9},
}