activity
20172022
most citedSubmodular Streaming in All its Glory: Tight Approximation, Minimum Memory and Low Adaptive Complexity

32 citations · 55 across the 12 of their papers we have counts for

collaborators

22 papers

cs.DS20221 cited

Efficient and Stable Fully Dynamic Facility Location

Sayan Bhattacharya, Silvio Lattanzi, Nikos Parotsidis

We consider the classic facility location problem in fully dynamic data streams, where elements can be both inserted and deleted. In this problem, one is interested in maintaining…

cs.LG20222 cited

On Classification Thresholds for Graph Attention with Edge Features

Kimon Fountoulakis, Dake He, Silvio Lattanzi +3

The recent years we have seen the rise of graph neural networks for prediction tasks on graphs. One of the dominant architectures is graph attention due to its ability to make pred…

cs.LG2022

Active Learning of Classifiers with Label and Seed Queries

Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi +2

We study exact active learning of binary and multiclass classifiers with margin. Given an -point set , we want to learn any unknown classifier on who…

cs.LG20223 cited

Near-Optimal Correlation Clustering with Privacy

Vincent Cohen-Addad, Chenglin Fan, Silvio Lattanzi +4

Correlation clustering is a central problem in unsupervised learning, with applications spanning community detection, duplicate detection, automated labelling and many more. In the…

cs.DS20213 cited

Correlation Clustering in Constant Many Parallel Rounds

Vincent Cohen-Addad, Silvio Lattanzi, Slobodan Mitrović +3

Correlation clustering is a central topic in unsupervised learning, with many applications in ML and data mining. In correlation clustering, one receives as input a signed graph an…

cs.LG2021

On Margin-Based Cluster Recovery with Oracle Queries

Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi +1

We study an active cluster recovery problem where, given a set of points and an oracle answering queries like "are these two points in the same cluster?", the task is to recove…