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» Handling variations and uncertainties
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IJCV
2002
188views more  IJCV 2002»
13 years 7 months ago
Scalable Extrinsic Calibration of Omni-Directional Image Networks
We describe a linear-time algorithm that recovers absolute camera orientations and positions, along with uncertainty estimates, for networks of terrestrial image nodes spanning hun...
Matthew E. Antone, Seth J. Teller
ML
2007
ACM
156views Machine Learning» more  ML 2007»
13 years 7 months ago
Active learning for logistic regression: an evaluation
Which active learning methods can we expect to yield good performance in learning binary and multi-category logistic regression classifiers? Addressing this question is a natural ...
Andrew I. Schein, Lyle H. Ungar
ICCV
2009
IEEE
13 years 5 months ago
A hybrid generative/discriminative classification framework based on free-energy terms
Hybrid generative-discriminative techniques and, in particular, generative score-space classification methods have proven to be valuable approaches in tackling difficult object or...
Alessandro Perina, Marco Cristani, Umberto Castell...
ISPASS
2008
IEEE
14 years 2 months ago
An Analysis of I/O And Syscalls In Critical Sections And Their Implications For Transactional Memory
Transactional memory (TM) is a scalable and concurrent way to build atomic sections. One aspect of TM that remains unclear is how side-effecting operations – that is, those whic...
Lee Baugh, Craig B. Zilles
ICDE
2012
IEEE
277views Database» more  ICDE 2012»
11 years 10 months ago
Aggregate Query Answering on Possibilistic Data with Cardinality Constraints
— Uncertainties in data arise for a number of reasons: when the data set is incomplete, contains conflicting information or has been deliberately perturbed or coarsened to remov...
Graham Cormode, Divesh Srivastava, Entong Shen, Ti...