OPT 2009: 2nd NIPS Workshop on Optimization for Machine Learning
Schedule: 12th December, 2009. PDF VERSION OF SCHEDULE
Time | Speaker | Title | Slides | Video | |
---|---|---|---|---|---|
07:30--08:20 | Lieven Vandenberghe | Invited Talk: Chordal sparsity in semidefinite programming and machine learning | [Slides] | ||
08:20--08:40 | S. D. Ahipasaoglu | A Pathwise Algorithm for Covariance Selection [.pdf] | [Slides] | ||
08:40--09:00 | Rodolphe Jenatton | Active Set Algorithm for Structured Sparsity-Inducing Norms [.pdf] | [Slides] | ||
09:00--09:25 | COFFEE BREAK | ||||
09:25--10:15 | Arkadi Nemirovski | Invited Talk: On recent trends in extremely large-scale convex optimization. | [Slides] | ||
10:15--10:30 | Poster Spotlights | ||||
10:30--15:30 | Long Break; Poster Session Begins | ||||
15:30--16:20 | Nathan Srebro | Invited Talk: From local steps to global convex optimization and back | [Slides] | [Video] | |
16:20--16:40 | Bertrand Cornélusse | Tree based ensemble models regularization by convex optimization. [.pdf] | [Slides] | ||
16:40--17:00 | Bharath Sriperumbudur | On the Convergence of the Convex-Concave procedure. [.pdf] | [Slides] | ||
17:00--17:20 | COFFEE BREAK | ||||
17:20--17:40 | Katya Scheinberg | SINCO - an Efficient Greedy Method for Learning Sparse INverse COvariance Matrix. [.pdf] | [Slides] | ||
17:40--18:00 | Ryota Tomioka | Super-Linear Convergence of Dual Augmented Lagrangian Algorithm for Sparse Learning. [.pdf] | [Slides] | ||
18:00--19:00 | Poster Session Continues |
Updates
Please don't forget to RegisterWorkshop Location: Hilton, Sutcliffe B
Workshop Date: 12.12.2009
Poster Spotlights
- Large Margin Classification with the Progressive Hedging Algorithm. Boris Defourny
- Bandit-Aided Boosting. Robert Busa-Fekete
- Mixed-Integer Support Vector Machine. Wei Guan
- Sampling-based optimization with mixtures. RĂ©mi Bardenet
- Variable Selection and Grouping with Multiple Graph Priors. Marco Signoretto
- Feature Selection as a one-player game. Romaric Gaudel
- A D.C. Programming Approach to the Sparse Generalized Eigenvalue Problem. Bharath Sriperumbudur