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