3 papers
cs.LG2024
Boosting, Voting Classifiers and Randomized Sample Compression Schemes
Arthur da Cunha, Kasper Green Larsen, Martin Ritzert
In boosting, we aim to leverage multiple weak learners to produce a strong learner. At the center of this paradigm lies the concept of building the strong learner as a voting class…
cs.LG2023
Polynomially Over-Parameterized Convolutional Neural Networks Contain Structured Strong Winning Lottery Tickets
Arthur da Cunha, Francesco d'Amore, Emanuele Natale
The Strong Lottery Ticket Hypothesis (SLTH) states that randomly-initialised neural networks likely contain subnetworks that perform well without any training. Although unstructure…
math.PR2022
Revisiting the Random Subset Sum problem
Arthur da Cunha, Francesco d'Amore, Frédéric Giroire +3
The average properties of the well-known Subset Sum Problem can be studied by the means of its randomised version, where we are given a target value , random variables $X_1, \ld…