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ECML
2003
Springer
15 years 11 months ago
Robust k-DNF Learning via Inductive Belief Merging
A central issue in logical concept induction is the prospect of inconsistency. This problem may arise due to noise in the training data, or because the target concept does not fit...
Frédéric Koriche, Joël Quinquet...
ECTEL
2009
Springer
15 years 11 months ago
Getting to Know Your User - Unobtrusive User Model Maintenance within Work-Integrated Learning Environments
Work-integrated learning (WIL) poses unique challenges for user model design: on the one hand users’ knowledge levels need to be determined based on their work activities – tes...
Stefanie N. Lindstaedt, Günter Beham, Barbara...
AAAI
2008
15 years 8 months ago
Adaptive Treatment of Epilepsy via Batch-mode Reinforcement Learning
This paper highlights the crucial role that modern machine learning techniques can play in the optimization of treatment strategies for patients with chronic disorders. In particu...
Arthur Guez, Robert D. Vincent, Massimo Avoli, Joe...
IJCAI
2007
15 years 8 months ago
Learning Policies for Embodied Virtual Agents through Demonstration
Although many powerful AI and machine learning techniques exist, it remains difficult to quickly create AI for embodied virtual agents that produces visually lifelike behavior. T...
Jonathan Dinerstein, Parris K. Egbert, Dan Ventura
AAAI
2006
15 years 7 months ago
Learning Blocking Schemes for Record Linkage
Record linkage is the process of matching records across data sets that refer to the same entity. One issue within record linkage is determining which record pairs to consider, si...
Matthew Michelson, Craig A. Knoblock