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» On Multiple Linear Approximations
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COLT
1999
Springer
15 years 8 months ago
Covering Numbers for Support Vector Machines
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Ro...
ICLP
1997
Springer
15 years 8 months ago
Non-Failure Analysis for Logic Programs
We provide a method whereby, given mode and (upper approximation) type information, we can detect procedures and goals that can be guaranteed to not fail (i.e., to produce at leas...
Saumya K. Debray, Pedro López-García...
EUROCRYPT
2004
Springer
15 years 7 months ago
Efficient Private Matching and Set Intersection
We consider the problem of computing the intersection of private datasets of two parties, where the datasets contain lists of elements taken from a large domain. This problem has m...
Michael J. Freedman, Kobbi Nissim, Benny Pinkas
AIPS
2007
15 years 6 months ago
Discovering Relational Domain Features for Probabilistic Planning
In sequential decision-making problems formulated as Markov decision processes, state-value function approximation using domain features is a critical technique for scaling up the...
Jia-Hong Wu, Robert Givan
AAAI
2008
15 years 6 months ago
Dimension Amnesic Pyramid Match Kernel
With the success of local features in object recognition, feature-set representations are widely used in computer vision and related domains. Pyramid match kernel (PMK) is an effi...
Yi Liu, Xulei Wang, Hongbin Zha