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» Measuring Complexity of Intelligent Machines
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ECML
2006
Springer
15 years 1 months ago
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Corneliu Henegar, Karine Clément, Jean-Dani...
IPL
2002
65views more  IPL 2002»
14 years 9 months ago
Parallel evolutionary algorithms can achieve super-linear performance
One of the main reasons for using parallel evolutionary algorithms (PEAs) is to obtain efficient algorithms with an execution time much lower than that of their sequential counter...
Enrique Alba
ALT
2006
Springer
15 years 6 months ago
Active Learning in the Non-realizable Case
Most of the existing active learning algorithms are based on the realizability assumption: The learner’s hypothesis class is assumed to contain a target function that perfectly c...
Matti Kääriäinen
ICML
2004
IEEE
15 years 10 months ago
Decision trees with minimal costs
We propose a simple, novel and yet effective method for building and testing decision trees that minimizes the sum of the misclassification and test costs. More specifically, we f...
Charles X. Ling, Qiang Yang, Jianning Wang, Shicha...
EMNLP
2010
14 years 7 months ago
Assessing Phrase-Based Translation Models with Oracle Decoding
Extant Statistical Machine Translation (SMT) systems are very complex softwares, which embed multiple layers of heuristics and embark very large numbers of numerical parameters. A...
Guillaume Wisniewski, Alexandre Allauzen, Fran&cce...