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TIDSE
2004
Springer
14 years 4 months ago
Learning from the Movie Industry: Adapting Production Processes for Storytelling in VR
Any movie production needs a whole group of contributing authors and creative artists from various fields. The same should obviously be true for the making of a compelling VR scena...
Richard Wages, Benno Grützmacher, Stefan Conr...
IUI
2005
ACM
14 years 4 months ago
Active preference learning for personalized calendar scheduling assistance
We present PLIANT, a learning system that supports adaptive assistance in an open calendaring system. PLIANT learns user preferences from the feedback that naturally occurs during...
Melinda T. Gervasio, Michael D. Moffitt, Martha E....
FLAIRS
2004
14 years 17 days ago
Cautious Cooperative Learning with Distributed Case-Based Reasoning
In this paper, we propose a cautious cooperative learning approach using distributed case-based reasoning. Our approach consists of two learning mechanisms: individual and coopera...
Leen-Kiat Soh
AGI
2011
13 years 2 months ago
Reinforcement Learning and the Bayesian Control Rule
We present an actor-critic scheme for reinforcement learning in complex domains. The main contribution is to show that planning and I/O dynamics can be separated such that an intra...
Pedro Alejandro Ortega, Daniel Alexander Braun, Si...
ICML
2005
IEEE
14 years 12 months ago
Supervised versus multiple instance learning: an empirical comparison
We empirically study the relationship between supervised and multiple instance (MI) learning. Algorithms to learn various concepts have been adapted to the MI representation. Howe...
Soumya Ray, Mark Craven