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SIGIR
2008
ACM
14 years 11 months ago
Learning from labeled features using generalized expectation criteria
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Gregory Druck, Gideon S. Mann, Andrew McCallum
ICANN
2009
Springer
15 years 6 months ago
Selective Attention Improves Learning
Abstract. We demonstrate that selective attention can improve learning. Considerably fewer samples are needed to learn a source separation problem when the inputs are pre-segmented...
Antti Yli-Krekola, Jaakko Särelä, Harri ...
ECCV
2004
Springer
16 years 1 months ago
Automatic Non-rigid 3D Modeling from Video
We present a robust framework for estimating non-rigid 3D shape and motion in video sequences. Given an input video sequence, and a user-specified region to reconstruct, the algori...
Lorenzo Torresani, Aaron Hertzmann
SOCRATES
2008
100views Education» more  SOCRATES 2008»
15 years 1 months ago
Quality in eLearning. Some Results from a National Research Program
Quality is an open concept. Something has a good quality when the most salient of its characteristics have a positive value. What are this relevant features? It depends on the int...
Patrizia Ghislandi, Anna Pedroni, Daniela Paolino,...
ICRA
2009
IEEE
111views Robotics» more  ICRA 2009»
15 years 6 months ago
Interactive learning of the acoustic properties of household objects
— Human beings can perceive object properties such as size, weight, and material type based solely on the sounds that the objects make when an action is performed on them. In ord...
Jivko Sinapov, Mark Wiemer, Alexander Stoytchev