Imitation is actively being studied as an effective means of learning in multi-agent environments. It allows an agent to learn how to act well (perhaps optimally) by passively obs...
E cient learning of DFA is a challenging research problem in grammatical inference. Both exact and approximate (in the PAC sense) identi ability of DFA from examples is known to b...
The problemofmultipleglobalcomparisonin familiesof biologicalsequences has been wellstudied. Fewer algorithms have been developed for identifying local consensus patterns or motif...
Yuh-Jyh Hu, Suzanne B. Sandmeyer, Dennis F. Kibler
The applicationofboosting procedures to decision tree algorithmshas been shown to produce very accurate classi ers. These classiers are in the form of a majority vote over a numbe...
Before applying learning algorithms to datasets, practitioners often globally discretize any numeric attributes. If the algorithm cannot handle numeric attributes directly, prior ...
ing from Robot Sensor Data using Hidden Markov Models Laura Firoiu, Paul Cohen Computer Science Department, LGRC University of Massachusetts at Amherst, Box 34610 Amherst, MA 01003...
AdaCost, a variant of AdaBoost, is a misclassification cost-sensitive boosting method. It uses the cost of misclassifications to update the training distribution on successive boo...
Wei Fan, Salvatore J. Stolfo, Junxin Zhang, Philip...