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» A Model of Inductive Bias Learning
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ACL
2009
13 years 6 months ago
Learning with Annotation Noise
It is usually assumed that the kind of noise existing in annotated data is random classification noise. Yet there is evidence that differences between annotators are not always ra...
Eyal Beigman, Beata Beigman Klebanov
AUSAI
2004
Springer
14 years 2 months ago
A Learning-Based Algorithm Selection Meta-reasoner for the Real-Time MPE Problem
Abstract. The algorithm selection problem aims to select the best algorithm for an input problem instance according to some characteristics of the instance. This paper presents a l...
Haipeng Guo, William H. Hsu
CLIMA
2004
13 years 10 months ago
The Apriori Stochastic Dependency Detection (ASDD) Algorithm for Learning Stochastic Logic Rules
Apriori Stochastic Dependency Detection (ASDD) is an algorithm for fast induction of stochastic logic rules from a database of observations made by an agent situated in an environm...
Christopher Child, Kostas Stathis
SLP
1989
105views more  SLP 1989»
13 years 9 months ago
Automatic Ordering of Subgoals - A Machine Learning Approach
This paper describes a learning system, LASSY1, which explores domains represented by Prolog databases, and use its acquired knowledge to increase the efficiency of a Prolog inter...
Shaul Markovitch, Paul D. Scott
ICML
2008
IEEE
14 years 9 months ago
Automatic discovery and transfer of MAXQ hierarchies
We present an algorithm, HI-MAT (Hierarchy Induction via Models And Trajectories), that discovers MAXQ task hierarchies by applying dynamic Bayesian network models to a successful...
Neville Mehta, Soumya Ray, Prasad Tadepalli, Thoma...