Poster Spotlights 1

**A Comparison of Inference Methods for Sparse Factor Analysis Models**\\ Oliver Stegle, Kevin Sharp, Magnus Rattray, John Winn **Generalization Bounds for Learning the Kernel: Rademacher Chaos Complexity**\\ Yiming Ying, Colin Campbell **Learning Non-Sparse Kernel Mixtures**\\ Marius Kloft, Ulf Brefeld, Soren Sonnenburg, Alexander Zien, Pavel Laskov, Klaus-Robert Muller **l1 regularization path for functional features**\\ Manuel Loth, Philippe Preux **Lq-regularised sparse classifiers: A PAC-Bayes analysis**\\ Ata Kaban **Robust Regression and Lasso**\\ Huan Xu, Constantine Caramanis, Shie Mannor **Selection in Functional ANOVA Models with Non-uniform Data**\\ Marco Signoretto, Kristiaan Pelckmans, Johan A.K. Suykens **Sparse and Interpretable Principal Components**\\ Doyo Gragn, Nickolay T. Trendafilov **Sparse multiscale spatial models of fMRI on irregular graphs**\\ Harrison L., Woods W., Green G. **Stagewise Polytope Faces Pursuit for Recovery of Sparse Representations**\\ Mark D. Plumbley, Marco Bevilacqua **Subspectral Algorithms for Sparse Learning**\\ Baback Moghaddam, Yair Weiss, Shai Avidan **Variable Selection and Sparsity Recovery via L1/2 Penalty**\\ Zongben Xu, Hai Zhang, Yao Wang, Xiangyu Chang