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CVPR
2009
IEEE
15 years 5 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...
ICML
2003
IEEE
14 years 10 months ago
Unsupervised Learning with Permuted Data
We consider the problem of unsupervised learning from a matrix of data vectors where in each row the observed values are randomly permuted in an unknown fashion. Such problems ari...
Sergey Kirshner, Sridevi Parise, Padhraic Smyth
ICML
2000
IEEE
14 years 10 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
VLDB
2007
ACM
130views Database» more  VLDB 2007»
14 years 10 months ago
A Simple and Efficient Estimation Method for Stream Expression Cardinalities
Estimating the cardinality (i.e. number of distinct elements) of an arbitrary set expression defined over multiple distributed streams is one of the most fundamental queries of in...
Aiyou Chen, Jin Cao, Tian Bu
SIGMOD
2007
ACM
169views Database» more  SIGMOD 2007»
14 years 10 months ago
Scalable approximate query processing with the DBO engine
This paper describes query processing in the DBO database system. Like other database systems designed for ad-hoc, analytic processing, DBO is able to compute the exact answer to ...
Christopher M. Jermaine, Subramanian Arumugam, Abh...