114 citations · 132 across the 12 of their papers we have counts for
10 papers · 1 filter
An Improved Uniform Convergence Bound with Fat-Shattering Dimension
Roberto Colomboni, Emmanuel Esposito, Andrea Paudice
The fat-shattering dimension characterizes the uniform convergence property of real-valued functions. The state-of-the-art upper bounds feature a multiplicative squared logarithmic…
Regret Analysis of Dyadic Search
François Bachoc, Tommaso Cesari, Roberto Colomboni +1
We analyze the cumulative regret of the Dyadic Search algorithm of Bachoc et al. [2022].
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…
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…
Multitask Online Mirror Descent
Nicolò Cesa-Bianchi, Pierre Laforgue, Andrea Paudice +1
We introduce and analyze MT-OMD, a multitask generalization of Online Mirror Descent (OMD) which operates by sharing updates between tasks. We prove that the regret of MT-OMD is of…
Exact Recovery of Clusters in Finite Metric Spaces Using Oracle Queries
Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi +1
We investigate the problem of exact cluster recovery using oracle queries. Previous results show that clusters in Euclidean spaces that are convex and separated with a margin can b…
Robust Unsupervised Learning via L-Statistic Minimization
Andreas Maurer, Daniela A. Parletta, Andrea Paudice +1
Designing learning algorithms that are resistant to perturbations of the underlying data distribution is a problem of wide practical and theoretical importance. We present a genera…
Exact Recovery of Mangled Clusters with Same-Cluster Queries
Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi +1
We study the cluster recovery problem in the semi-supervised active clustering framework. Given a finite set of input points, and an oracle revealing whether any two points lie in…
Correlation Clustering with Adaptive Similarity Queries
Marco Bressan, Nicolò Cesa-Bianchi, Andrea Paudice +1
In correlation clustering, we are given objects together with a binary similarity score between each pair of them. The goal is to partition the objects into clusters so to mini…
Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization
Luis Muñoz-González, Battista Biggio, Ambra Demontis +4
A number of online services nowadays rely upon machine learning to extract valuable information from data collected in the wild. This exposes learning algorithms to the threat of d…