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ML
2006
ACM
122views Machine Learning» more  ML 2006»
13 years 8 months ago
PRL: A probabilistic relational language
In this paper, we describe the syntax and semantics for a probabilistic relational language (PRL). PRL is a recasting of recent work in Probabilistic Relational Models (PRMs) into ...
Lise Getoor, John Grant
POPL
2012
ACM
12 years 4 months ago
Recursive proofs for inductive tree data-structures
We develop logical mechanisms and decision procedures to facilitate the verification of full functional properties of inductive tree data-structures using recursion that are soun...
Parthasarathy Madhusudan, Xiaokang Qiu, Andrei Ste...
ILP
2005
Springer
14 years 2 months ago
Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models
Abstract. Logical Bayesian Networks (LBNs) have recently been introduced as another language for knowledge based model construction of Bayesian networks, besides existing languages...
Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe...
FLAIRS
2001
13 years 10 months ago
Graph-Based Concept Learning
We introduce the graph-based relational concept learner SubdueCL. We start with a brief description of other graph-based learning systems: the Galois lattice, Conceptual Graphs, a...
Jesus A. Gonzalez, Lawrence B. Holder, Diane J. Co...
SEMWEB
2010
Springer
13 years 6 months ago
Towards Semantic Annotation Supported by Dependency Linguistics and ILP
In this paper we present a method for semantic annotation of texts, which is based on a deep linguistic analysis (DLA) and Inductive Logic Programming (ILP). The combination of DLA...
Jan Dedek