43 citations · 92 across the 21 of their papers we have counts for
26 papers
Dimension-Free Rank Lifting from Random Hyperplane Arrangements
Luca Becchetti, Matteo Russo, Ruben Skorupinski
We study the width required for a randomly initialized hidden layer of a neural network to achieve rank lifting. Namely, given a dataset of , …
A Tour of Locality Sensitive Filtering on the Sphere
Luca Becchetti, Andrea Clementi, Luciano Gualà +3
The Approximate Near Neighbor (ANN) problem is a cornerstone of high-dimensional data analysis. While Locality Sensitive Hashing (LSH) has been the classical paradigm, recent work…
Approximate -hop neighborhoods on incremental graphs: An efficient lazy approach
Luca Becchetti, Andrea Clementi, Luciano Gualà +3
In this work, we propose, analyze and empirically validate a lazy-update approach to maintain accurate approximations of the -hop neighborhoods of dynamic graphs resulting from…
The Minority Dynamics and the Power of Synchronicity
Luca Becchetti, Andrea Clementi, Francesco Pasquale +3
We study the minority-opinion dynamics over a fully-connected network of nodes with binary opinions. Upon activation, a node receives a sample of opinions from a limited number…
On a Voter Model with Context-Dependent Opinion Adoption
Luca Becchetti, Vincenzo Bonifaci, Emilio Cruciani +1
Opinion diffusion is a crucial phenomenon in social networks, often underlying the way in which a collective of agents develops a consensus on relevant decisions. The voter model i…
On the Role of Memory in Robust Opinion Dynamics
Luca Becchetti, Andrea Clementi, Amos Korman +3
We investigate opinion dynamics in a fully-connected system, consisting of identical and anonymous agents, where one of the opinions (which is called correct) represents a piec…
Biological Random Walks: multi-omics integration for disease gene prioritization
Michele Gentili, Leonardo Martini, Marialuisa Sponziello +1
Motivation: Over the past decade, network-based approaches have proven useful in identifying disease modules within the human interactome, often providing insights into key mechani…
Network Based Approach to Gene Prioritization at Genome-Wide Association Study Loci
Leonardo Martini, Adriano Fazzone, Michele Gentili +2
Motivation: Genome-wide association studies (GWAS) have successfully identified thousands of genetic risk loci for complex traits and diseases. Most of these GWAS loci lie in regul…
On the Multidimensional Random Subset Sum Problem
Luca Becchetti, Arthur Carvalho Walraven da Cunha, Andrea Clementi +4
In the Random Subset Sum Problem, given i.i.d. random variables , we wish to approximate any point as the sum of a suitable subset $X_{i_1(z)}, ..…
Bond Percolation in Small-World Graphs with Power-Law Distribution
Luca Becchetti, Andrea Clementi, Francesco Pasquale +2
\emph{Full-bond percolation} with parameter is the process in which, given a graph, for every edge independently, we delete the edge with probability . Bond percolation is…
Network and Sequence-Based Prediction of Protein-Protein Interactions
Leonardo Martini, Adriano Fazzone, Luca Becchetti
Background:Typically, proteins perform key biological functions by interacting with each other. As a consequence, predicting which protein pairs interact is a fundamental problem.…
Percolation and Epidemic Processes in One-Dimensional Small-World Networks
Luca Becchetti, Andrea Clementi, Riccardo Denni +3
We obtain tight thresholds for bond percolation on one-dimensional small-world graphs, and apply such results to obtain tight thresholds for the \emph{Independent Cascade} process…
Biased Opinion Dynamics: When the Devil Is in the Details
Aris Anagnostopoulos, Luca Becchetti, Emilio Cruciani +2
We investigate opinion dynamics in multi-agent networks when a bias toward one of two possible opinions exists; for example, reflecting a status quo vs a superior alternative. Star…
Expansion and Flooding in Dynamic Random Networks with Node Churn
Luca Becchetti, Andrea Clementi, Francesco Pasquale +2
We study expansion and information diffusion in dynamic networks, that is in networks in which nodes and edges are continuously created and destroyed. We consider information diffu…
Biological Random Walks: integrating heterogeneous data in disease gene prioritization
Michele Gentili, Leonardo Martini, Manuela Petti +2
This work proposes a unified framework to leverage biological information in network propagation-based gene prioritization algorithms. Preliminary results on breast cancer data sho…
Principal Fairness: Removing Bias via Projections
Aris Anagnostopoulos, Luca Becchetti, Adriano Fazzone +2
Reducing hidden bias in the data and ensuring fairness in algorithmic data analysis has recently received significant attention. We complement several recent papers in this line of…
Finding a Bounded-Degree Expander Inside a Dense One
Luca Becchetti, Andrea Clementi, Emanuele Natale +2
It follows from the Marcus-Spielman-Srivastava proof of the Kadison-Singer conjecture that if is a -regular dense expander then there is an edge-induced subgraph $H=(V…
Pooling or Sampling: Collective Dynamics for Electrical Flow Estimation
Luca Becchetti, Vincenzo Bonifaci, Emanuele Natale
The computation of electrical flows is a crucial primitive for many recently proposed optimization algorithms on weighted networks. While typically implemented as a centralized sub…
Average whenever you meet: Opportunistic protocols for community detection
Luca Becchetti, Andrea Clementi, Pasin Manurangsi +4
Consider the following asynchronous, opportunistic communication model over a graph : in each round, one edge is activated uniformly and independently at random and (only) its t…
Find Your Place: Simple Distributed Algorithms for Community Detection
Luca Becchetti, Andrea Clementi, Emanuele Natale +2
Given an underlying graph, we consider the following \emph{dynamics}: Initially, each node locally chooses a value in , uniformly at random and independently of other nod…
Stabilizing Consensus with Many Opinions
Luca Becchetti, Andrea Clementi, Emanuele Natale +2
We consider the following distributed consensus problem: Each node in a complete communication network of size initially holds an \emph{opinion}, which is chosen arbitrarily fr…
Probabilistic Self-Stabilization
Luca Becchetti, Andrea Clementi, Emanuele Natale +1
By using concrete scenarios, we present and discuss a new concept of probabilistic Self-Stabilization in Distributed Systems.
Self-Stabilizing Repeated Balls-into-Bins
Luca Becchetti, Andrea Clementi, Emanuele Natale +2
We study the following synchronous process that we call "repeated balls-into-bins". The process is started by assigning balls to bins in an arbitrary way. In every subseque…
Plurality Consensus in the Gossip Model
L. Becchetti, A. Clementi, E. Natale +2
We study Plurality Consensus in the Gossip Model over a network of anonymous agents. Each agent supports an initial opinion or color. We assume that at the onset, the number of…