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» Learning Submodular Functions
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74
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COLT
2007
Springer
15 years 4 months ago
How Good Is a Kernel When Used as a Similarity Measure?
Recently, Balcan and Blum [1] suggested a theory of learning based on general similarity functions, instead of positive semi-definite kernels. We study the gap between the learnin...
Nathan Srebro
82
Voted
BMCBI
2008
100views more  BMCBI 2008»
14 years 10 months ago
High-precision high-coverage functional inference from integrated data sources
Background: Information obtained from diverse data sources can be combined in a principled manner using various machine learning methods to increase the reliability and range of k...
Bolan Linghu, Evan S. Snitkin, Dustin T. Holloway,...
IJCNN
2008
IEEE
15 years 4 months ago
Numerical condition of feedforward networks with opposite transfer functions
— Numerical condition affects the learning speed and accuracy of most artificial neural network learning algorithms. In this paper, we examine the influence of opposite transfe...
Mario Ventresca, Hamid R. Tizhoosh
72
Voted
DAGSTUHL
1994
14 years 11 months ago
Function-Based Object Recognition
Functionality-based recognition systems recognize objects at the category level by reasoning about how well the objects support the expected function. Such systems naturally assoc...
Louise Stark, Kevin W. Bowyer
76
Voted
GECCO
2007
Springer
187views Optimization» more  GECCO 2007»
15 years 4 months ago
Defining implicit objective functions for design problems
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examp...
Sean Hanna