Arthur da Cunha

According to our database, Arthur da Cunha authored at least 10 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Sample-Near-Optimal Agnostic Boosting with Improved Running Time.

Arthur da Cunha, Mikael Møller Høgsgaard, Andrea Paudice

CoRR, January, 2026

2025

Revisiting Agnostic Boosting.

Arthur da Cunha, Mikael Møller Høgsgaard, Andrea Paudice, Yuxin Sun

CoRR, March, 2025

Boosting, Voting Classifiers and Randomized Sample Compression Schemes.

Arthur da Cunha, Kasper Green Larsen, Martin Ritzert

Proceedings of the International Conference on Algorithmic Learning Theory, 2025

2024

Optimal Parallelization of Boosting.

Arthur da Cunha, Mikael Møller Høgsgaard, Kasper Green Larsen

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Pruning random structures. (Élagage des structures aléatoires).

Arthur Carvalho Walraven da Cunha

PhD thesis, 2023

Neural Network Information Leakage Through Hidden Learning.

Arthur Carvalho Walraven da Cunha, Emanuele Natale, Laurent Viennot

Proceedings of the Optimization and Learning - 6th International Conference, 2023

Polynomially Over-Parameterized Convolutional Neural Networks Contain Structured Strong Winning Lottery Tickets.

Arthur da Cunha, Francesco d'Amore, Emanuele Natale

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Revisiting the Random Subset Sum Problem.

Arthur Carvalho Walraven da Cunha, Francesco d'Amore, Frédéric Giroire, Hicham Lesfari, Emanuele Natale, Laurent Viennot

Proceedings of the 31st Annual European Symposium on Algorithms, 2023

2022

On the Multidimensional Random Subset Sum Problem.

Luca Becchetti, Arthur Carvalho Walraven da Cunha, Andrea Clementi, Francesco d'Amore, Hicham Lesfari, Emanuele Natale, Luca Trevisan

CoRR, 2022

Proving the Lottery Ticket Hypothesis for Convolutional Neural Networks.

Arthur da Cunha, Emanuele Natale, Laurent Viennot

Proceedings of the Tenth International Conference on Learning Representations, 2022