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105
Voted
PRL
2006
106views more  PRL 2006»
15 years 1 months ago
Invariances in kernel methods: From samples to objects
This paper presents a general method for incorporating prior knowledge into kernel methods such as Support Vector Machines. It applies when the prior knowledge can be formalized b...
Alexei Pozdnoukhov, Samy Bengio
109
Voted
ML
2008
ACM
162views Machine Learning» more  ML 2008»
15 years 1 months ago
Incorporating prior knowledge in support vector regression
This paper explores the addition of constraints to the linear programming formulation of the support vector regression problem for the incorporation of prior knowledge. Equality an...
Fabien Lauer, Gérard Bloch
109
Voted
JAIR
2006
113views more  JAIR 2006»
15 years 1 months ago
Generative Prior Knowledge for Discriminative Classification
We present a novel framework for integrating prior knowledge into discriminative classifiers. Our framework allows discriminative classifiers such as Support Vector Machines (SVMs...
Arkady Epshteyn, Gerald DeJong
94
Voted
IJAR
2006
118views more  IJAR 2006»
15 years 1 months ago
Learning Bayesian network parameters under order constraints
We consider the problem of learning the parameters of a Bayesian network from data, while taking into account prior knowledge about the signs of influences between variables. Such...
A. J. Feelders, Linda C. van der Gaag
91
Voted
IEICET
2008
95views more  IEICET 2008»
15 years 1 months ago
Approximating the Best Linear Unbiased Estimator of Non-Gaussian Signals with Gaussian Noise
Obtaining the best linear unbiased estimator (BLUE) of noisy signals is a traditional but powerful approach to noise reduction. Explicitly computing the BLUE usually requires the ...
Masashi Sugiyama, Motoaki Kawanabe, Gilles Blancha...
114
Voted
AUTOMATICA
2006
103views more  AUTOMATICA 2006»
15 years 1 months ago
A universal iterative learning stabilizer for a class of MIMO systems
Design of iterative learning control (ILC) often requires some prior knowledge about a system's control matrix. In some applications, such as uncalibrated visual servoing, th...
Ping Jiang, Huadong Chen, Leon C. A. Bamforth
123
Voted
BMCBI
2010
154views more  BMCBI 2010»
15 years 1 months ago
Candidate gene prioritization by network analysis of differential expression using machine learning approaches
Background: Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available...
Daniela Nitsch, Joana P. Gonçalves, Fabian ...
96
Voted
ICASSP
2010
IEEE
15 years 1 months ago
Adaptive search for sparse targets with informative priors
ACT This works considers the problem of efficient energy allocation of resources in a continuous fashion in determining the location of targets in a sparse environment. We extend ...
Gregory Newstadt, Eran Bashan, Alfred O. Hero III
84
Voted
ICASSP
2010
IEEE
15 years 1 months ago
Cover song detection: From high scores to general classification
Existing cover song detection systems require prior knowledge of the number of cover songs in a test set in order to identify cover(s) to a reference song. We describe a system th...
Suman Ravuri, Daniel P. W. Ellis
105
Voted
ICA
2010
Springer
15 years 2 months ago
Use of Prior Knowledge in a Non-Gaussian Method for Learning Linear Structural Equation Models
Abstract. We discuss causal structure learning based on linear structural equation models. Conventional learning methods most often assume Gaussianity and create many indistinguish...
Takanori Inazumi, Shohei Shimizu, Takashi Washio