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» Detecting Inconsistencies in Distributed Data
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KDD
2009
ACM
189views Data Mining» more  KDD 2009»
14 years 3 months ago
CoCo: coding cost for parameter-free outlier detection
How can we automatically spot all outstanding observations in a data set? This question arises in a large variety of applications, e.g. in economy, biology and medicine. Existing ...
Christian Böhm, Katrin Haegler, Nikola S. M&u...
CORR
2008
Springer
92views Education» more  CORR 2008»
13 years 9 months ago
Catching Up Faster by Switching Sooner: A Prequential Solution to the AIC-BIC Dilemma
Bayesian model averaging, model selection and its approximations such as BIC are generally statistically consistent, but sometimes achieve slower rates of convergence than other m...
Tim van Erven, Peter Grünwald, Steven de Rooi...
BMCBI
2007
200views more  BMCBI 2007»
13 years 9 months ago
Assessment of algorithms for high throughput detection of genomic copy number variation in oligonucleotide microarray data
Background: Genomic deletions and duplications are important in the pathogenesis of diseases, such as cancer and mental retardation, and have recently been shown to occur frequent...
Ágnes Baross, Allen D. Delaney, H. Irene Li...
KDD
2003
ACM
127views Data Mining» more  KDD 2003»
14 years 9 months ago
Towards NIC-based intrusion detection
We present and evaluate a NIC-based network intrusion detection system. Intrusion detection at the NIC makes the system potentially tamper-proof and is naturally extensible to wor...
Matthew Eric Otey, Srinivasan Parthasarathy, Amol ...
ICS
1993
Tsinghua U.
14 years 1 months ago
Static and Dynamic Evaluation of Data Dependence Analysis
—Data dependence analysis techniques are the main component of today’s strategies for automatic detection of parallelism. Parallelism detection strategies are being incorporate...
Paul Petersen, David A. Padua