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» Evaluating algorithms that learn from data streams
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SIGMOD
2006
ACM
150views Database» more  SIGMOD 2006»
16 years 4 months ago
On-the-fly sharing for streamed aggregation
Data streaming systems are becoming essential for monitoring applications such as financial analysis and network intrusion detection. These systems often have to process many simi...
Sailesh Krishnamurthy, Chung Wu, Michael J. Frankl...
LREC
2008
155views Education» more  LREC 2008»
15 years 5 months ago
L-ISA: Learning Domain Specific Isa-Relations from the Web
Automated extraction of ontological knowledge from text corpora is a relevant task in Natural Language Processing. In this paper, we focus on the problem of finding hypernyms for ...
Alessandra Potrich, Emanuele Pianta
KDD
2004
ACM
330views Data Mining» more  KDD 2004»
16 years 4 months ago
Learning to detect malicious executables in the wild
In this paper, we describe the development of a fielded application for detecting malicious executables in the wild. We gathered 1971 benign and 1651 malicious executables and enc...
Jeremy Z. Kolter, Marcus A. Maloof
ICDM
2008
IEEE
145views Data Mining» more  ICDM 2008»
15 years 11 months ago
Paired Learners for Concept Drift
To cope with concept drift, we paired a stable online learner with a reactive one. A stable learner predicts based on all of its experience, whereas a reactive learner predicts ba...
Stephen H. Bach, Marcus A. Maloof
EGH
2010
Springer
15 years 2 months ago
GPU random numbers via the tiny encryption algorithm
Random numbers are extensively used on the GPU. As more computation is ported to the GPU, it can no longer be treated as rendering hardware alone. Random number generators (RNG) a...
Fahad Zafar, Marc Olano, Aaron Curtis