39 citations · 129 across the 23 of their papers we have counts for
7 papers · 1 filter
Distributed k-Means with Outliers in General Metrics
Enrico Dandolo, Andrea Pietracaprina, Geppino Pucci
Center-based clustering is a pivotal primitive for unsupervised learning and data analysis. A popular variant is undoubtedly the k-means problem, which, given a set of points f…
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…
Accurate MapReduce Algorithms for -median and -means in General Metric Spaces
Alessio Mazzetto, 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 -median and -mean…
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…