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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...
ISMAR
2009
IEEE
16 years 1 months ago
Real-time in-situ visual feedback of task performance in mixed environments for learning joint psychomotor-cognitive tasks
This paper proposes an approach to mixed environment training of manual tasks requiring concurrent use of psychomotor and cognitive skills. To train concurrent use of both skill s...
Aaron Kotranza, D. Scott Lind, Carla M. Pugh, Benj...
BMCBI
2010
113views more  BMCBI 2010»
15 years 7 months ago
Unifying generative and discriminative learning principles
Background: The recognition of functional binding sites in genomic DNA remains one of the fundamental challenges of genome research. During the last decades, a plethora of differe...
Jens Keilwagen, Jan Grau, Stefan Posch, Marc Stric...
AAAI
2006
15 years 8 months ago
On Multi-Class Cost-Sensitive Learning
Rescaling is possibly the most popular approach to cost-sensitive learning. This approach works by rescaling the classes according to their costs, and it can be realized in differ...
Zhi-Hua Zhou, Xu-Ying Liu