Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...
We present a new algorithm, called LB-Triang, which computes minimal triangulations. We give both a straightforward O(nm0) time implementation and a more involved O(nm) time imple...
Anne Berry, Jean Paul Bordat, Pinar Heggernes, Gen...
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
Recent works showed how low-density parity-check (LDPC) erasure correcting codes, under maximum likelihood (ML) decoding, are capable of tightly approaching the performance of an i...
Enrico Paolini, Gianluigi Liva, Michela Varrella, ...
We survey results on transitive-closure spanners and their applications. Given a directed graph G = (V, E) and an integer k 1, a k-transitive-closure-spanner (k-TC-spanner) of G ...