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EMNLP
2008
15 years 8 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
COGSCI
2010
64views more  COGSCI 2010»
15 years 6 months ago
A One-to-One Bias and Fast Mapping Support Preschoolers' Learning About Faces and Voices
A multi-modal person representation contains information about what a person looks like and what a person sounds like. However, little is known about how children form these face-...
Mariko Moher, Lisa Feigenson, Justin Halberda
SIGCSE
2002
ACM
202views Education» more  SIGCSE 2002»
15 years 6 months ago
A tutorial program for propositional logic with human/computer interactive learning
This paper describes a tutorial program that serves a double role as an educational tool and a research environment. First, it introduces students to fundamental concepts of propo...
Stacy Lukins, Alan Levicki, Jennifer Burg
CVPR
2008
IEEE
16 years 8 months ago
Discriminative learning of visual words for 3D human pose estimation
This paper addresses the problem of recovering 3D human pose from a single monocular image, using a discriminative bag-of-words approach. In previous work, the visual words are le...
Huazhong Ning, Wei Xu, Yihong Gong, Thomas S. Huan...
AMAI
2004
Springer
16 years 1 days ago
Using the Central Limit Theorem for Belief Network Learning
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
Ian Davidson, Minoo Aminian