Many signals of interest are corrupted by faults of an unknown type. We propose an approach that uses Gaussian processes and a general “fault bucket” to capture a priori uncha...
Michael A. Osborne, Roman Garnett, Kevin Swersky, ...
Abstract Polynomial-time data reduction is a classical approach to hard graph problems. Typically, particular small subgraphs are replaced by smaller gadgets. We generalize this ap...
Abstract. In this paper, we study lower bound techniques for branchand-bound algorithms for maximum parsimony, with a focus on gene order data. We give a simple O(n3 ) time dynamic...
Abraham Bachrach, Kevin Chen, Chris Harrelson, Rad...
The largeness and the heterogeneity of most graph-modeled datasets in several database application areas make the query process a real challenge because of the lack of a complete ...
Federica Mandreoli, Riccardo Martoglia, Giorgio Vi...
Identifying the patterns of large data sets is a key requirement in data mining. A powerful technique for this purpose is the principal component analysis (PCA). PCA-based clusteri...