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ICML
2007
IEEE
14 years 9 months ago
A kernel-based causal learning algorithm
We describe a causal learning method, which employs measuring the strength of statistical dependences in terms of the Hilbert-Schmidt norm of kernel-based cross-covariance operato...
Xiaohai Sun, Dominik Janzing, Bernhard Schölk...
ICML
2007
IEEE
14 years 9 months ago
Classifying matrices with a spectral regularization
We propose a method for the classification of matrices. We use a linear classifier with a novel regularization scheme based on the spectral 1-norm of its coefficient matrix. The s...
Ryota Tomioka, Kazuyuki Aihara
ICML
2008
IEEE
14 years 9 months ago
Multi-task compressive sensing with Dirichlet process priors
Compressive sensing (CS) is an emerging field that, under appropriate conditions, can significantly reduce the number of measurements required for a given signal. In many applicat...
Yuting Qi, Dehong Liu, David B. Dunson, Lawrence C...
ICML
2008
IEEE
14 years 9 months ago
Extracting and composing robust features with denoising autoencoders
Previous work has shown that the difficulties in learning deep generative or discriminative models can be overcome by an initial unsupervised learning step that maps inputs to use...
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pi...
ICML
2006
IEEE
14 years 9 months ago
Kernelizing the output of tree-based methods
We extend tree-based methods to the prediction of structured outputs using a kernelization of the algorithm that allows one to grow trees as soon as a kernel can be defined on the...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...