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CVPR
2009
IEEE
16 years 11 months ago
Co-training with Noisy Perceptual Observations
Many perception and multimedia indexing problems involve datasets that are naturally comprised of multiple streams or modalities for which supervised training data is only sparsely...
Ashish Kapoor, Chris Mario Christoudias, Raquel Ur...
133
Voted
ICIP
2006
IEEE
16 years 5 months ago
Support Vector Machines for Camera Calibration Problem
This paper presents a statistical learning-based solution to the camera calibration problem in which the Support Vector Machines (SVM) are used for the estimation of the projectio...
Refaat M. Mohamed, Abdelrehim H. Ahmed, Ahmed Eid,...
118
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ICML
2009
IEEE
16 years 4 months ago
Detecting the direction of causal time series
We propose a method that detects the true direction of time series, by fitting an autoregressive moving average model to the data. Whenever the noise is independent of the previou...
Arthur Gretton, Bernhard Schölkopf, Dominik J...
JMLR
2002
87views more  JMLR 2002»
15 years 3 months ago
Shallow Parsing using Noisy and Non-Stationary Training Material
Shallow parsers are usually assumed to be trained on noise-free material, drawn from the same distribution as the testing material. However, when either the training set is noisy ...
Miles Osborne
140
Voted
ICDM
2005
IEEE
122views Data Mining» more  ICDM 2005»
15 years 9 months ago
Learning through Changes: An Empirical Study of Dynamic Behaviors of Probability Estimation Trees
In practice, learning from data is often hampered by the limited training examples. In this paper, as the size of training data varies, we empirically investigate several probabil...
Kun Zhang, Zujia Xu, Jing Peng, Bill P. Buckles