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AAAI
2010
13 years 9 months ago
Structure Learning for Markov Logic Networks with Many Descriptive Attributes
Many machine learning applications that involve relational databases incorporate first-order logic and probability. Markov Logic Networks (MLNs) are a prominent statistical relati...
Hassan Khosravi, Oliver Schulte, Tong Man, Xiaoyua...
ML
2000
ACM
103views Machine Learning» more  ML 2000»
13 years 7 months ago
Phase Transitions in Relational Learning
One of the major limitations of relational learning is due to the complexity of verifying hypotheses on examples. In this paper we investigate this task in light of recent publishe...
Attilio Giordana, Lorenza Saitta
AIMSA
2008
Springer
14 years 2 months ago
Incorporating Learning in Grid-Based Randomized SAT Solving
Abstract. Computational Grids provide a widely distributed computing environment suitable for randomized SAT solving. This paper develops techniques for incorporating learning, kno...
Antti Eero Johannes Hyvärinen, Tommi A. Juntt...
ICML
1994
IEEE
13 years 11 months ago
Reducing Misclassification Costs
We explore algorithms for learning classification procedures that attempt to minimize the cost of misclassifying examples. First, we consider inductive learning of classification ...
Michael J. Pazzani, Christopher J. Merz, Patrick M...
ECML
2003
Springer
14 years 28 days ago
A New Way to Introduce Knowledge into Reinforcement Learning
We present in this paper a method to introduce a priori knowledge into reinforcement learning using temporally extended actions. The aim of our work is to reduce the learning time ...
Pascal Garcia