Friday December 9th, 2005
The workshop has attracted a large number of high quality submissions. Rather than limiting the number of presentations, we have chosen to organize a poster session. The choice ``talk or poster'' was partly constrained by prior engagements and is not meant to suggest any difference in quality.
Morning session: 7:30am--10:30am
| 7:30am | Welcome |
| 7:40am | Working Set Selection Using the Second Order Information for SVMs Chih-Jen Lin |
| 8:00am | Large-scale parallel implementations of SVMs Hans-Peter Graf, Igor Durdanovic, Eric Cosatto |
| 8:20am | Online Learning with a Memory Harness Ofer Dekel, Shai Shalev-Schwartz, Yoram Singer |
| 8:40am | Poster spotlights |
| 9:00am | Coffee break and Poster setup |
| 9:10am | Implementing SVM in an RDBMS: Improved Scalability and Usability Joseph S. Yarmus, Boriana L. Milenova, Marcos M. Campos |
| 9:30am | Large Scale Genomic Sequence Support Vector Machines Soren Sonnenburg, Gunnar Rätsch |
| 9:50am | Improved Fast Gauss Transform Ramani Duraiswami, Vikas Raykar |
| 10:10am | Approximate Methods for Gaussian Process Regression Chris Williams, Joaquin Quiñonero Candela, Carl Rasmussen |
Afternoon session: 3:30pm--6:30pm
| 3:30pm | Trading Convexity for Scalability Ronan Collobert, Jason Weston |
| 3:50pm | Fast greedy algorithms for building sparse kernel machines Sathiya Keerthi |
| 4:10pm | Online SVM Learning with SMD Gain Adaptation Nic Schraudolph, S.V.N. Vishwanathan, Alex Smola |
| 4:30pm | Coffee Break and Posters: Simple and SimplerSVM S. V. N. Vishwanathan A parallel training algorithm for large scale support vector machines Elad Tom-Yov Fast Transpose Methods for Sparse Kernel Learning Patrick Haffner "Dual consistency" for training methods in kernel methods Gökhan Bakır On-line Learning with Sparse Kernels for Video Analysis Li Cheng, Shaojun Wang, Dale Schuurmans, Terry Caelli Very Large Scale Manifold Regularization using Core Vector Machines Ivor W. Tsang, James T. Kwok Kernel ICA for Large Scale Problems Stephanie Jegelka, Arthur Gretton, Dimitris Achlioptas Distributed objects applied to Support Vector Machines Joannes Vermorel |
| 5:20pm | The Curse of Learning Complicated Functions using Local Kernels Yoshua Bengio |
| 5:40pm | LASVM applied to large invariant problems Gaelle Loosli |
| 6:00pm | Learning large-scale tasks with complicated invariances: Why kernel methods fall short Yann LeCun |
| 6:20pm | Discussion and Concluding remarks |