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KDD
2010
ACM
272views Data Mining» more  KDD 2010»
15 years 5 months ago
Beyond heuristics: learning to classify vulnerabilities and predict exploits
The security demands on modern system administration are enormous and getting worse. Chief among these demands, administrators must monitor the continual ongoing disclosure of sof...
Mehran Bozorgi, Lawrence K. Saul, Stefan Savage, G...
ICDM
2007
IEEE
148views Data Mining» more  ICDM 2007»
15 years 5 months ago
Sample Selection for Maximal Diversity
The problem of selecting a sample subset sufficient to preserve diversity arises in many applications. One example is in the design of recombinant inbred lines (RIL) for genetic a...
Feng Pan, Adam Roberts, Leonard McMillan, David Th...
CIKM
2008
Springer
15 years 3 months ago
Learning a two-stage SVM/CRF sequence classifier
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Guilherme Hoefel, Charles Elkan
SDM
2004
SIAM
214views Data Mining» more  SDM 2004»
15 years 2 months ago
Making Time-Series Classification More Accurate Using Learned Constraints
It has long been known that Dynamic Time Warping (DTW) is superior to Euclidean distance for classification and clustering of time series. However, until lately, most research has...
Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
SISAP
2010
IEEE
135views Data Mining» more  SISAP 2010»
14 years 11 months ago
Improving the similarity search of tandem mass spectra using metric access methods
In biological applications, the tandem mass spectrometry is a widely used method for determining protein and peptide sequences from an ”in vitro” sample. The sequences are not...
Jiri Novák, Tomás Skopal, David Hoks...