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COLT
2008
Springer
15 years 9 months ago
Learning in the Limit with Adversarial Disturbances
We study distribution-dependent, data-dependent, learning in the limit with adversarial disturbance. We consider an optimization-based approach to learning binary classifiers from...
Constantine Caramanis, Shie Mannor
NIPS
2008
15 years 8 months ago
Efficient Sampling for Gaussian Process Inference using Control Variables
Sampling functions in Gaussian process (GP) models is challenging because of the highly correlated posterior distribution. We describe an efficient Markov chain Monte Carlo algori...
Michalis Titsias, Neil D. Lawrence, Magnus Rattray
ICVGIP
2004
15 years 8 months ago
On Learning Shapes from Shades
Shape from Shading (SFS) is one of the most extensively studied problems in Computer Vision. However, most of the approaches only deal with Lambertian or other specific shading mo...
Subhajit Sanyal, Mayank Bansal, Subhashis Banerjee...
DICTA
2003
15 years 8 months ago
A Robust Method for Estimating the Fundamental Matrix
In this paper, we propose a robust method to estimate the fundamental matrix in the presence of outliers. The new method uses random minimum subsets as a search engine to find inli...
C. L. Feng, Y. S. Hung
ICASSP
2010
IEEE
15 years 7 months ago
Noise robust exemplar-based connected digit recognition
This paper proposes a noise robust exemplar-based speech recognition system where noisy speech is modeled as a linear combination of a set of speech and noise exemplars. The metho...
Jort F. Gemmeke, Tuomas Virtanen