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JMLR
2010
155views more  JMLR 2010»
13 years 6 months ago
Approximate Tree Kernels
Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pa...
Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Ro...
CVPR
2011
IEEE
13 years 4 months ago
On Deep Generative Models with Applications to Recognition
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Marc', Aurelio Ranzato, Joshua Susskind, Volodymyr...
WWW
2011
ACM
13 years 2 months ago
Heat-seeking honeypots: design and experience
Many malicious activities on the Web today make use of compromised Web servers, because these servers often have high pageranks and provide free resources. Attackers are therefore...
John P. John, Fang Yu, Yinglian Xie, Arvind Krishn...
JMLR
2010
106views more  JMLR 2010»
13 years 2 months ago
Why Does Unsupervised Pre-training Help Deep Learning?
Much recent research has been devoted to learning algorithms for deep architectures such as Deep Belief Networks and stacks of auto-encoder variants, with impressive results obtai...
Dumitru Erhan, Yoshua Bengio, Aaron C. Courville, ...
ICASSP
2011
IEEE
12 years 11 months ago
Sparse graphical modeling of piecewise-stationary time series
Graphical models are useful for capturing interdependencies of statistical variables in various fields. Estimating parameters describing sparse graphical models of stationary mul...
Daniele Angelosante, Georgios B. Giannakis