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» Learning action effects in partially observable domains
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EMNLP
2008
14 years 11 months ago
Modeling Annotators: A Generative Approach to Learning from Annotator Rationales
A human annotator can provide hints to a machine learner by highlighting contextual "rationales" for each of his or her annotations (Zaidan et al., 2007). How can one ex...
Omar Zaidan, Jason Eisner
POPL
2009
ACM
15 years 10 months ago
Feedback-directed barrier optimization in a strongly isolated STM
Speed improvements in today's processors have largely been delivered in the form of multiple cores, increasing the importance of ions that ease parallel programming. Software...
Nathan Grasso Bronson, Christos Kozyrakis, Kunle O...
ICIP
2008
IEEE
15 years 4 months ago
Level set tracking with dynamical shape priors
Dynamical shape priors are curical for level set-based nonrigid object tracking with noise, occlusions or background clutter. In this paper, we propose a level set tracking framew...
Xue Zhou, Xi Li, Weiming Hu
ICPR
2006
IEEE
15 years 10 months ago
Bayesian Imitation of Human Behavior in Interactive Computer Games
Modern interactive computer games provide the ability to objectively record complex human behavior, offering a variety of interesting challenges to the pattern-recognition communi...
Bernard Gorman, Christian Bauckhage, Christian Thu...
ATAL
2008
Springer
14 years 11 months ago
Modeling parallel and reactive empathy in virtual agents: an inductive approach
Humans continuously assess one another's situational context, modify their own affective state, and then respond based on these outcomes through empathetic expression. Virtua...
Scott W. McQuiggan, Jennifer L. Robison, Robert Ph...