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NIPS
2000
15 years 8 months ago
Learning Joint Statistical Models for Audio-Visual Fusion and Segregation
People can understand complex auditory and visual information, often using one to disambiguate the other. Automated analysis, even at a lowlevel, faces severe challenges, includin...
John W. Fisher III, Trevor Darrell, William T. Fre...
ICML
2010
IEEE
15 years 8 months ago
Learning Fast Approximations of Sparse Coding
In Sparse Coding (SC), input vectors are reconstructed using a sparse linear combination of basis vectors. SC has become a popular method for extracting features from data. For a ...
Karol Gregor, Yann LeCun
CSCW
2008
ACM
15 years 7 months ago
Sotto Voce:  Facilitating Social Learning in a Historic House
This study examines visitors' use of two different electronic guidebook prototypes, the second an iteration of the first, that were developed to support social interaction bet...
Margaret H. Szymanski, Paul M. Aoki, Rebecca E. Gr...
IJCV
2007
196views more  IJCV 2007»
15 years 6 months ago
Weakly Supervised Scale-Invariant Learning of Models for Visual Recognition
We investigate a method for learning object categories in a weakly supervised manner. Given a set of images known to contain the target category from a similar viewpoint, learning...
Robert Fergus, Pietro Perona, Andrew Zisserman
ESOP
2011
Springer
14 years 10 months ago
Measure Transformer Semantics for Bayesian Machine Learning
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Johannes Borgström, Andrew D. Gordon, Michael...