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SIAMIS
2010
156views more  SIAMIS 2010»
14 years 10 months ago
Learning the Morphological Diversity
This article proposes a new method for image separation into a linear combination of morphological components. Sparsity in fixed dictionaries is used to extract the cartoon and osc...
Gabriel Peyré, Jalal Fadili, Jean-Luc Starc...
CICC
2011
106views more  CICC 2011»
14 years 3 months ago
A 45nm CMOS neuromorphic chip with a scalable architecture for learning in networks of spiking neurons
Efforts to achieve the long-standing dream of realizing scalable learning algorithms for networks of spiking neurons in silicon have been hampered by (a) the limited scalability of...
Jae-sun Seo, Bernard Brezzo, Yong Liu, Benjamin D....
KDD
2005
ACM
158views Data Mining» more  KDD 2005»
16 years 3 months ago
Adversarial learning
Many classification tasks, such as spam filtering, intrusion detection, and terrorism detection, are complicated by an adversary who wishes to avoid detection. Previous work on ad...
Daniel Lowd, Christopher Meek
ICML
2007
IEEE
16 years 4 months ago
Discriminative learning for differing training and test distributions
We address classification problems for which the training instances are governed by a distribution that is allowed to differ arbitrarily from the test distribution--problems also ...
Michael Brückner, Steffen Bickel, Tobias Sche...
ICML
2005
IEEE
16 years 4 months ago
Preference learning with Gaussian processes
In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relat...
Wei Chu, Zoubin Ghahramani