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» Machine Learning of Higher Order Programs
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ICML
2007
IEEE
16 years 12 days ago
Learning from interpretations: a rooted kernel for ordered hypergraphs
The paper presents a kernel for learning from ordered hypergraphs, a formalization that captures relational data as used in Inductive Logic Programming (ILP). The kernel generaliz...
Gabriel Wachman, Roni Khardon
AIIA
2005
Springer
15 years 5 months ago
Handling Continuous-Valued Attributes in Incremental First-Order Rules Learning
Machine Learning systems are often distinguished according to the kind of representation they use, which can be either propositional or first-order logic. The framework working wi...
Teresa Maria Altomare Basile, Floriana Esposito, N...
ALT
2004
Springer
15 years 8 months ago
Probabilistic Inductive Logic Programming
Probabilistic inductive logic programming, sometimes also called statistical relational learning, addresses one of the central questions of artificial intelligence: the integratio...
Luc De Raedt, Kristian Kersting
IJCNN
2006
IEEE
15 years 5 months ago
Learning the Kernel in Mahalanobis One-Class Support Vector Machines
— In this paper, we show that one-class SVMs can also utilize data covariance in a robust manner to improve performance. Furthermore, by constraining the desired kernel function ...
Ivor W. Tsang, James T. Kwok, Shutao Li
SCP
1998
113views more  SCP 1998»
14 years 11 months ago
Linear-Time Hierarchies for a Functional Language Machine Model
In STOC 93, Jones sketched the existence of a hierarchy within problems decidable in linear time by a first-order functional language based on tree-structured data (F), as well a...
Eva Rose