AI & Statistics 2005

Poster Session 2

Friday January 7 

 

1. Restricted concentration models – graphical Gaussian models with concentration parameters restricted to being equal
   Søren Højsgaard and Steffen Lauritzen
   
2. Focused Inference
   Romer Rosales and Tommi Jaakkola
   
3. Online (and Offline) on an Even Tighter Budget
   Jason Weston, Antoine Bordes and Leon Bottou
   
4. A Uniform Convergence Bound for the Area Under the ROC Curve
   Shivani Agarwal, Sariel Har-Peled and Dan Roth
   
5. Very Large SVM Training using Core Vector Machines
   Ivor Tsang, James Kwok and Pak-Ming Cheung
   
6. OOBN for Forensic Identification through Searching a DNA profiles’ Database
   David Cavallini and Fabio Corradi
   
7. On the Behavior of MDL Denoising
   Teemu Roos, Petri Myllymäki and Henry Tirri
   
8. Efficient Non-Parametric Function Induction in Semi-Supervised Learning
   Olivier Delalleau, Yoshua Bengio and Nicolas Le Roux
   
9. Hierarchical Probabilistic Neural Network Language Model
   Frederic Morin and Yoshua Bengio
   
10. Deformable Spectrograms
    Manuel Reyes-Gomez, Nebojsa Jojic and Daniel Ellis
    
11. On Contrastive Divergence Learning
    Miguel Á. Carreira-Perpiñán and Geoffrey Hinton
    
12. Learning in Markov Random Fields with Contrastive Free Energies
    Max Welling and Charles Sutton