OPT 2009: 2nd NIPS Workshop on Optimization for Machine Learning

Accepted Papers

  1. Large Margin Classification with the Progressive Hedging Algorithm.    Boris Defourny; Louis Wehenkel
  2. Bandit-Aided Boosting.    Robert Busa-Fekete; Balazs Kegl
  3. A Pathwise Algorithm for Covariance Selection.    Vijay Krishnamurthy; Selin Ahipasaoglu; Alexandre d'Aspremont
  4. Super-Linear Convergence of Dual Augmented Lagrangian Algorithm for Sparse Learning.    Ryota Tomioka; Taiji Suzuki; Masashi Sugiyama
  5. Active Set Algorithm for Structured Sparsity-Inducing Norms.    Rodolphe Jenatton; Jean-Yves Audibert; Francis Bach
  6. Mixed-Integer Support Vector Machine.    Wei Guan; Alexander Gray; Sven Leyffer
  7. On the convergence of the concave-convex procedure.    Bharath Sriperumbudur; Gert Lanckriet
  8. Tree based ensemble models regularization by convex optimization.    Bertrand CornĂ©lusse; Pierre Geurts; Louis Wehenkel
  9. Sampling-based optimization with mixtures.    RĂ©mi Bardenet; Balazs Kegl
  10. Variable Selection and Grouping with Multiple Graph Priors.    Marco Signoretto; Anneleen Daemen; Carlo Savorgnan; Johan Suykens
  11. Feature Selection as a one-player game.    Romaric Gaudel; Michele Sebag
  12. A D.C. Programming Approach to the Sparse Generalized Eigenvalue Problem.    Bharath Sriperumbudur; David Torres; Gert Lanckriet
  13. SINCO - an Efficient Greedy Method for Learning Sparse INverse COvariance Matrix.    Katya Scheinberg; Irina Rish



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