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» On Random Sampling over Joins
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ICASSP
2008
IEEE
15 years 8 months ago
Finding needles in noisy haystacks
The theory of compressed sensing shows that samples in the form of random projections are optimal for recovering sparse signals in high-dimensional spaces (i.e., finding needles ...
Rui M. Castro, Jarvis Haupt, Robert Nowak, Gil M. ...
132
Voted
AIPS
2009
15 years 3 months ago
Computing Robust Plans in Continuous Domains
We define the robustness of a sequential plan as the probability that it will execute successfully despite uncertainty in the execution environment. We consider a rich notion of u...
Christian Fritz, Sheila A. McIlraith
IJSN
2007
73views more  IJSN 2007»
15 years 1 months ago
Optimal worm-scanning method using vulnerable-host distributions
: Most Internet worms use random scanning. The distribution of vulnerable hosts on the Internet, however, is highly non-uniform over the IP-address space. This implies that random ...
Zesheng Chen, Chuanyi Ji
96
Voted
PKDD
2007
Springer
91views Data Mining» more  PKDD 2007»
15 years 8 months ago
Domain Adaptation of Conditional Probability Models Via Feature Subsetting
The goal in domain adaptation is to train a model using labeled data sampled from a domain different from the target domain on which the model will be deployed. We exploit unlabel...
Sandeepkumar Satpal, Sunita Sarawagi
MM
1999
ACM
117views Multimedia» more  MM 1999»
15 years 6 months ago
NAIVE - network aware Internet video encoding
The distribution of digital video content over computer networks has become commonplace. Unfortunately, most digital video encoding standards do not degrade gracefully in the face...
Héctor M. Briceño, Steven J. Gortler...