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HRI
2006
ACM
16 years 20 days ago
Using context and sensory data to learn first and second person pronouns
We present a method of grounded word learning that is powerful enough to learn the meanings of first and second person pronouns. The model uses the understood words in an utteran...
Kevin Gold, Brian Scassellati
NIPS
1994
15 years 8 months ago
Catastrophic Interference in Human Motor Learning
Biological sensorimotor systems are not static maps that transform input sensory information into output motor behavior. Evidence from many lines of research suggests that their r...
Tom Brashers-Krug, Reza Shadmehr, Emanuel Todorov
ITS
2010
Springer
178views Multimedia» more  ITS 2010»
15 years 11 months ago
Learning What Works in ITS from Non-traditional Randomized Controlled Trial Data
The traditional, well established approach to finding out what works in education research is to run a randomized controlled trial (RCT) using a standard pretest and posttest desig...
Zachary A. Pardos, Matthew D. Dailey, Neil T. Heff...
ICCV
2011
IEEE
14 years 6 months ago
From Learning Models of Natural Image Patches to Whole Image Restoration
Learning good image priors is of utmost importance for the study of vision, computer vision and image processing applications. Learning priors and optimizing over whole images can...
Daniel Zoran, Yair Weiss
AAAI
2006
15 years 8 months ago
Learning Systems of Concepts with an Infinite Relational Model
Relationships between concepts account for a large proportion of semantic knowledge. We present a nonparametric Bayesian model that discovers systems of related concepts. Given da...
Charles Kemp, Joshua B. Tenenbaum, Thomas L. Griff...