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ICLP
1997
Springer
15 years 2 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...
NN
1997
Springer
174views Neural Networks» more  NN 1997»
15 years 2 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani
EUROCRYPT
2004
Springer
15 years 1 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 13 days 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 13 days 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