2 citations · 9 across the 10 of their papers we have counts for
6 papers · 1 filter
A General Coreset-Based Approach to Diversity Maximization under Matroid Constraints
Matteo Ceccarello, Andrea Pietracaprina, Geppino Pucci
Diversity maximization is a fundamental problem in web search and data mining. For a given dataset of elements, the problem requires to determine a subset of containing…
Solving -center Clustering (with Outliers) in MapReduce and Streaming, almost as Accurately as Sequentially
Matteo Ceccarello, Andrea Pietracaprina, Geppino Pucci
Center-based clustering is a fundamental primitive for data analysis and becomes very challenging for large datasets. In this paper, we focus on the popular -center variant whic…
MapReduce and Streaming Algorithms for Diversity Maximization in Metric Spaces of Bounded Doubling Dimension
Matteo Ceccarello, Andrea Pietracaprina, Geppino Pucci +1
Given a dataset of points in a metric space and an integer , a diversity maximization problem requires determining a subset of points maximizing some diversity objective mea…
A Practical Parallel Algorithm for Diameter Approximation of Massive Weighted Graphs
Matteo Ceccarello, Andrea Pietracaprina, Geppino Pucci +1
We present a space and time efficient practical parallel algorithm for approximating the diameter of massive weighted undirected graphs on distributed platforms supporting a MapRed…
Experimental Evaluation of Multi-Round Matrix Multiplication on MapReduce
Matteo Ceccarello, Francesco Silvestri
A common approach in the design of MapReduce algorithms is to minimize the number of rounds. Indeed, there are many examples in the literature of monolithic MapReduce algorithms, w…
Space and Time Efficient Parallel Graph Decomposition, Clustering, and Diameter Approximation
Matteo Ceccarello, Andrea Pietracaprina, Geppino Pucci +1
We develop a novel parallel decomposition strategy for unweighted, undirected graphs, based on growing disjoint connected clusters from batches of centers progressively selected fr…