Papers
Ellipsoidal Support Vector Machines
Michinari Momma, Kohei Hatano, Hiroki Nakayama
Learning Polyhedral Classifiers Using Logistic Function
Naresh Manwani, P. S. Sastry
Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors
Alessandro Chiuso, Gianluigi Pillonetto
Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition
Serhat Bucak, Rong Jin, Anil K. Jain
Robust PCA via Outlier Pursuit
Huan Xu, Constantine Caramanis, Sujay Sanghavi
Learning To Count Objects in Images
Victor Lempitsky, Andrew Zisserman
Fast detection of multiple change-points shared by many signals using group LARS
Jean-philippe Vert, Kevin Bleakley
An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA
Matthias Hein, Thomas Bühler
Learning invariant features using the Transformed Indian Buffet Process
Joseph L. Austerweil, Thomas L. Griffiths
Copula Processes
Andrew G Wilson, Zoubin Ghahramani
Probabilistic Inference and Differential Privacy
Oliver Williams, Frank Mcsherry
Distributed Dual Averaging In Networks
Alekh Agarwal, Martin J. Wainwright, John C. Duchi
Implicit encoding of prior probabilities in optimal neural populations
Deep Ganguli, Eero P. Simoncelli
Towards Property-Based Classification of Clustering Paradigms
Margareta Ackerman, Shai Ben-David, David Loker
Layered image motion with explicit occlusions, temporal consistency, and depth ordering
Deqing Sun, Erik B. Sudderth, Michael J. Black
The LASSO risk: asymptotic results and real world examples
Mohsen Bayati, José Pereira, Andrea Montanari
Functional form of motion priors in human motion perception
Hongjing Lu, Tungyou Lin, Alan Lee et al.
Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear Models
Felipe Gerhard, Wulfram Gerstner
Spatial and anatomical regularization of SVM for brain image analysis
Remi Cuingnet, Marie Chupin, Habib Benali et al.
Monte-Carlo Planning in Large POMDPs
David Silver, Joel Veness
Learning via Gaussian Herding
Koby Crammer, Daniel D. Lee