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ICCV
2011
IEEE
8 years 5 months ago
Discriminative Learning of Relaxed Hierarchy for Large-scale Visual Recognition
In the real visual world, the number of categories a classifier needs to discriminate is on the order of hundreds or thousands. For example, the SUN dataset [24] contains 899 sce...
Tianshi Gao, Daphne Koller
ICANN
2011
Springer
8 years 9 months ago
Learning Curves for Gaussian Processes via Numerical Cubature Integration
This paper is concerned with estimation of learning curves for Gaussian process regression with multidimensional numerical integration. We propose an approach where the recursion e...
Simo Särkkä
ICASSP
2011
IEEE
8 years 9 months ago
Spatially-correlated sensor discriminant analysis
A study of generalization error in signal detection by multiple spatially-distributed and -correlated sensors is provided when the detection rule is learned from a finite number ...
Kush R. Varshney
ML
2010
ACM
163views Machine Learning» more  ML 2010»
9 years 20 days ago
Classification with guaranteed probability of error
We introduce a general-purpose learning machine that we call the Guaranteed Error Machine, or GEM, and two learning algorithms, a real GEM algorithm and an ideal GEM algorithm. Th...
Marco C. Campi
JMLR
2010
125views more  JMLR 2010»
9 years 20 days ago
Stochastic Complexity and Generalization Error of a Restricted Boltzmann Machine in Bayesian Estimation
In this paper, we consider the asymptotic form of the generalization error for the restricted Boltzmann machine in Bayesian estimation. It has been shown that obtaining the maximu...
Miki Aoyagi
TCS
2011
9 years 25 days ago
Smart PAC-learners
The PAC-learning model is distribution-independent in the sense that the learner must reach a learning goal with a limited number of labeled random examples without any prior know...
Malte Darnstädt, Hans-Ulrich Simon
TCS
2010
9 years 4 months ago
Maximal width learning of binary functions
This paper concerns learning binary-valued functions defined on IR, and investigates how a particular type of ‘regularity’ of hypotheses can be used to obtain better generali...
Martin Anthony, Joel Ratsaby
NN
2002
Springer
224views Neural Networks» more  NN 2002»
9 years 5 months ago
Optimal design of regularization term and regularization parameter by subspace information criterion
The problem of designing the regularization term and regularization parameter for linear regression models is discussed. Previously, we derived an approximation to the generalizat...
Masashi Sugiyama, Hidemitsu Ogawa
ML
2002
ACM
133views Machine Learning» more  ML 2002»
9 years 5 months ago
Estimating Generalization Error on Two-Class Datasets Using Out-of-Bag Estimates
For two-class datasets, we provide a method for estimating the generalization error of a bag using out-of-bag estimates. In bagging, each predictor (single hypothesis) is learned ...
Tom Bylander
JMLR
2002
137views more  JMLR 2002»
9 years 5 months ago
The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces
A central problem in learning is selection of an appropriate model. This is typically done by estimating the unknown generalization errors of a set of models to be selected from a...
Masashi Sugiyama, Klaus-Robert Müller
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