The value 1 problem is a decision problem for probabilistic automata on finite words: given a probabilistic automaton A, are there words accepted by A with probability arbitraril...
This paper presents two metrics for the Nearest Neighbor Classifier that share the property of being adapted, i.e. learned, on a set of data. Both metrics can be used for similari...
When equipped with kernel functions, online learning algorithms are susceptible to the "curse of kernelization" that causes unbounded growth in the model size. To addres...
Abstract-- We present a new, biologically-inspired algorithm for the problem of covering a given region with wireless "units" (sensors or base-stations). The general prob...
For two-class datasets, we provide a method for estimating the generalization error of a bag using out-of-bag estimates. In bagging, each predictor (single hypothesis) is learned ...