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WWW
2005
ACM
16 years 5 months ago
LSH forest: self-tuning indexes for similarity search
We consider the problem of indexing high-dimensional data for answering (approximate) similarity-search queries. Similarity indexes prove to be important in a wide variety of sett...
Mayank Bawa, Tyson Condie, Prasanna Ganesan
ICFP
2009
ACM
16 years 5 months ago
Effective interactive proofs for higher-order imperative programs
We present a new approach for constructing and verifying higherorder, imperative programs using the Coq proof assistant. We build on the past work on the Ynot system, which is bas...
Adam J. Chlipala, J. Gregory Malecha, Greg Morrise...
KDD
2008
ACM
138views Data Mining» more  KDD 2008»
16 years 5 months ago
Quantitative evaluation of approximate frequent pattern mining algorithms
Traditional association mining algorithms use a strict definition of support that requires every item in a frequent itemset to occur in each supporting transaction. In real-life d...
Rohit Gupta, Gang Fang, Blayne Field, Michael Stei...
KDD
2008
ACM
172views Data Mining» more  KDD 2008»
16 years 5 months ago
Structured metric learning for high dimensional problems
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Jason V. Davis, Inderjit S. Dhillon
KDD
2002
ACM
157views Data Mining» more  KDD 2002»
16 years 5 months ago
Learning nonstationary models of normal network traffic for detecting novel attacks
Traditional intrusion detection systems (IDS) detect attacks by comparing current behavior to signatures of known attacks. One main drawback is the inability of detecting new atta...
Matthew V. Mahoney, Philip K. Chan