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STACS
1999
Springer
13 years 12 months ago
A Complete and Tight Average-Case Analysis of Learning Monomials
Abstract. We advocate to analyze the average complexity of learning problems. An appropriate framework for this purpose is introduced. Based on it we consider the problem of learni...
Rüdiger Reischuk, Thomas Zeugmann
CONCUR
1997
Springer
13 years 12 months ago
Reachability Analysis of Pushdown Automata: Application to Model-Checking
We apply the symbolic analysis principle to pushdown systems. We represent (possibly in nite) sets of con gurations of such systems by means of nite-state automata. In order to re...
Ahmed Bouajjani, Javier Esparza, Oded Maler
TSP
2008
117views more  TSP 2008»
13 years 7 months ago
A Theory for Sampling Signals From a Union of Subspaces
One of the fundamental assumptions in traditional sampling theorems is that the signals to be sampled come from a single vector space (e.g. bandlimited functions). However, in many...
Yue M. Lu, Minh N. Do
CVPR
2011
IEEE
13 years 5 months ago
Sparsity-based Image Denoising via Dictionary Learning and Structural Clustering
Where does the sparsity in image signals come from? Local and nonlocal image models have supplied complementary views toward the regularity in natural images the former attempts t...
Weisheng Dong, Xin Li
CIKM
2010
Springer
13 years 5 months ago
Regularization and feature selection for networked features
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
Hongliang Fei, Brian Quanz, Jun Huan