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» Evaluating algorithms that learn from data streams
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KCAP
2009
ACM
16 years 1 months ago
Interactively shaping agents via human reinforcement: the TAMER framework
As computational learning agents move into domains that incur real costs (e.g., autonomous driving or financial investment), it will be necessary to learn good policies without n...
W. Bradley Knox, Peter Stone
BMCBI
2010
166views more  BMCBI 2010»
15 years 6 months ago
Accurate peak list extraction from proteomic mass spectra for identification and profiling studies
Background: Mass spectrometry is an essential technique in proteomics both to identify the proteins of a biological sample and to compare proteomic profiles of different samples. ...
Nicola Barbarini, Paolo Magni
FUZZIEEE
2007
IEEE
16 years 1 months ago
Genetic Learning of Membership Functions for Mining Fuzzy Association Rules
— Data mining is most commonly used in attempts to induce association rules from transaction data. Most previous studies focused on binary-valued transaction data. Transaction da...
Rafael Alcalá, Jesús Alcalá-F...
SP
2010
IEEE
140views Security Privacy» more  SP 2010»
15 years 10 months ago
Inspector Gadget: Automated Extraction of Proprietary Gadgets from Malware Binaries
Abstract—Unfortunately, malicious software is still an unsolved problem and a major threat on the Internet. An important component in the fight against malicious software is the...
Clemens Kolbitsch, Thorsten Holz, Christopher Krue...
EMNLP
2010
15 years 4 months ago
Efficient Graph-Based Semi-Supervised Learning of Structured Tagging Models
We describe a new scalable algorithm for semi-supervised training of conditional random fields (CRF) and its application to partof-speech (POS) tagging. The algorithm uses a simil...
Amarnag Subramanya, Slav Petrov, Fernando Pereira