Alessandro De Palma

According to our database, Alessandro De Palma authored at least 15 papers between 2017 and 2024.

Collaborative distances:

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

2024

Scaling the Convex Barrier with Sparse Dual Algorithms.

Alessandro De Palma, Harkirat Singh Behl, Rudy Bunel, Philip H. S. Torr, M. Pawan Kumar

J. Mach. Learn. Res., 2024

On Using Certified Training towards Empirical Robustness.

Alessandro De Palma, Serge Durand, Zakaria Chihani, François Terrier, Caterina Urban

CoRR, 2024

Verified Neural Compressed Sensing.

Rudy Bunel, Krishnamurthy Dvijotham, M. Pawan Kumar, Alessandro De Palma, Robert Stanforth

CoRR, 2024

Expressive Losses for Verified Robustness via Convex Combinations.

Alessandro De Palma, Rudy Bunel, Krishnamurthy (Dj) Dvijotham, M. Pawan Kumar, Robert Stanforth, Alessio Lomuscio

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Verification of Geometric Robustness of Neural Networks via Piecewise Linear Approximation and Lipschitz Optimisation.

Ben Batten, Yang Zheng, Alessandro De Palma, Panagiotis Kouvaros, Alessio Lomuscio

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2022

IBP Regularization for Verified Adversarial Robustness via Branch-and-Bound.

Alessandro De Palma, Rudy Bunel, Krishnamurthy Dvijotham, M. Pawan Kumar, Robert Stanforth

CoRR, 2022

In Defense of the Unitary Scalarization for Deep Multi-Task Learning.

Vitaly Kurin, Alessandro De Palma, Ilya Kostrikov, Shimon Whiteson, M. Pawan Kumar

CoRR, 2022

In Defense of the Unitary Scalarization for Deep Multi-Task Learning.

Vitaly Kurin, Alessandro De Palma, Ilya Kostrikov, Shimon Whiteson, Pawan Kumar Mudigonda

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Improved Branch and Bound for Neural Network Verification via Lagrangian Decomposition.

Alessandro De Palma, Rudy Bunel, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar

CoRR, 2021

Scaling the Convex Barrier with Active Sets.

Alessandro De Palma, Harkirat S. Behl, Rudy Bunel, Philip H. S. Torr, M. Pawan Kumar

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Lagrangian Decomposition for Neural Network Verification.

Rudy Bunel, Alessandro De Palma, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

2019

Sampling Acquisition Functions for Batch Bayesian Optimization.

Alessandro De Palma, Celestine Mendler-Dünner, Thomas P. Parnell, Andreea Anghel, Haralampos Pozidis

CoRR, 2019

2018

Benchmarking and Optimization of Gradient Boosted Decision Tree Algorithms.

Andreea Anghel, Nikolaos Papandreou, Thomas P. Parnell, Alessandro De Palma, Haralampos Pozidis

CoRR, 2018

Communication-avoiding parallel minimum cuts and connected components.

Lukas Gianinazzi, Pavel Kalvoda, Alessandro De Palma, Maciej Besta, Torsten Hoefler

Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2018

2017

Distributed Stratified Locality Sensitive Hashing for Critical Event Prediction in the Cloud.

Alessandro De Palma, Erik Hemberg, Una-May O'Reilly

CoRR, 2017