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IDA
2005
Springer
14 years 2 months ago
Learning from Ambiguously Labeled Examples
Inducing a classification function from a set of examples in the form of labeled instances is a standard problem in supervised machine learning. In this paper, we are concerned w...
Eyke Hüllermeier, Jürgen Beringer
BMCBI
2008
85views more  BMCBI 2008»
13 years 8 months ago
Merging microarray data from separate breast cancer studies provides a robust prognostic test
Background: There is an urgent need for new prognostic markers of breast cancer metastases to ensure that newly diagnosed patients receive appropriate therapy. Recent studies have...
Lei Xu, Aik Choon Tan, Raimond L. Winslow, Donald ...
PAMI
2006
145views more  PAMI 2006»
13 years 8 months ago
Reflectance Sharing: Predicting Appearance from a Sparse Set of Images of a Known Shape
Three-dimensional appearance models consisting of spatially varying reflectance functions defined on a known shape can be used in analysis-by-synthesis approaches to a number of vi...
Todd Zickler, Ravi Ramamoorthi, Sebastian Enrique,...
ICML
2009
IEEE
14 years 9 months ago
Proto-predictive representation of states with simple recurrent temporal-difference networks
We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...
Takaki Makino
AUSAI
2003
Springer
14 years 1 months ago
Choosing Learning Algorithms Using Sign Tests with High Replicability
An important task in machine learning is determining which learning algorithm works best for a given data set. When the amount of data is small the same data needs to be used repea...
Remco R. Bouckaert