We study the Kolmogorov complexity of a Binary Insertion Tree, and present a succinct encoding scheme for Binary Insertion Trees produced from incompressible permutations. Based o...
We study the average number of transitions in Glushkov automata built from random regular expressions. This statistic highly depends on the probabilistic distribution set on the e...
We provide a worst-case analysis of selective sampling algorithms for learning linear threshold functions. The algorithms considered in this paper are Perceptron-like algorithms, ...
A selective sampling algorithm is a learning algorithm for classification that, based on the past observed data, decides whether to ask the label of each new instance to be classi...
We consider pixel labeling problems where the label set
forms a tree, and where the observations are also labels.
Such problems arise in feature-space analysis with a very
large...
Pedro Felzenszwalb, Gyula Pap, Eva Tardos, Ramin Z...