We extend the well-known BFGS quasi-Newton method and its memory-limited variant LBFGS to the optimization of nonsmooth convex objectives. This is done in a rigorous fashion by ge...
We present a method for reducing the treewidth of a graph while preserving all the minimal s−t separators. This technique turns out to be very useful in the design of parameteriz...
— In this contribution a feature selection method in semi-supervised problems is proposed. This method selects variables using a feature clustering strategy, using a combination ...
Abstract. We present hardness results, approximation heuristics, and exact algorithms for bottleneck labeled optimization problems arising in the context of graph theory. This long...
In the “query-by-humming” problem, we attempt to retrieve a specific song from a target set based on a sung query. Recent evaluations of query-by-humming systems show that th...