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ORCIDAlessandro De Palma
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2020 – today
- 2024
[j1]Alessandro De Palma, Harkirat Singh Behl, Rudy Bunel, Philip H. S. Torr, M. Pawan Kumar:
Scaling the Convex Barrier with Sparse Dual Algorithms. J. Mach. Learn. Res. 25: 61:1-61:51 (2024)- [c6]Ben Batten, Yang Zheng, Alessandro De Palma, Panagiotis Kouvaros, Alessio Lomuscio:
Verification of Geometric Robustness of Neural Networks via Piecewise Linear Approximation and Lipschitz Optimisation. ECAI 2024: 2362-2369 - [c5]Alessandro De Palma, Rudy Bunel, Krishnamurthy (Dj) Dvijotham, M. Pawan Kumar, Robert Stanforth, Alessio Lomuscio:
Expressive Losses for Verified Robustness via Convex Combinations. ICLR 2024 - [i12]Rudy Bunel, Krishnamurthy Dvijotham, M. Pawan Kumar, Alessandro De Palma, Robert Stanforth:
Verified Neural Compressed Sensing. CoRR abs/2405.04260 (2024) - [i11]Ben Batten, Yang Zheng, Alessandro De Palma, Panagiotis Kouvaros, Alessio Lomuscio:
Verification of Geometric Robustness of Neural Networks via Piecewise Linear Approximation and Lipschitz Optimisation. CoRR abs/2408.13140 (2024) - [i10]Alessandro De Palma, Serge Durand, Zakaria Chihani, François Terrier, Caterina Urban:
On Using Certified Training towards Empirical Robustness. CoRR abs/2410.01617 (2024) - 2023
- [i9]Alessandro De Palma, Rudy Bunel, Krishnamurthy Dvijotham, M. Pawan Kumar, Robert Stanforth, Alessio Lomuscio:
Expressive Losses for Verified Robustness via Convex Combinations. CoRR abs/2305.13991 (2023) - 2022
- [c4]Vitaly Kurin, Alessandro De Palma, Ilya Kostrikov, Shimon Whiteson, Pawan Kumar Mudigonda:
In Defense of the Unitary Scalarization for Deep Multi-Task Learning. NeurIPS 2022 - [i8]Vitaly Kurin, Alessandro De Palma, Ilya Kostrikov, Shimon Whiteson, M. Pawan Kumar:
In Defense of the Unitary Scalarization for Deep Multi-Task Learning. CoRR abs/2201.04122 (2022) - [i7]Alessandro De Palma, Rudy Bunel, Krishnamurthy Dvijotham, M. Pawan Kumar, Robert Stanforth:
IBP Regularization for Verified Adversarial Robustness via Branch-and-Bound. CoRR abs/2206.14772 (2022) - 2021
- [c3]Alessandro De Palma, Harkirat S. Behl, Rudy Bunel, Philip H. S. Torr, M. Pawan Kumar:
Scaling the Convex Barrier with Active Sets. ICLR 2021 - [i6]Alessandro De Palma, Harkirat Singh Behl, Rudy Bunel, Philip H. S. Torr, M. Pawan Kumar:
Scaling the Convex Barrier with Sparse Dual Algorithms. CoRR abs/2101.05844 (2021) - [i5]Alessandro De Palma, Rudy Bunel, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar:
Improved Branch and Bound for Neural Network Verification via Lagrangian Decomposition. CoRR abs/2104.06718 (2021) - 2020
- [c2]Rudy Bunel, Alessandro De Palma, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar:
Lagrangian Decomposition for Neural Network Verification. UAI 2020: 370-379 - [i4]Rudy Bunel, Alessandro De Palma, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar:
Lagrangian Decomposition for Neural Network Verification. CoRR abs/2002.10410 (2020)
2010 – 2019
- 2019
- [i3]Alessandro De Palma, Celestine Mendler-Dünner, Thomas P. Parnell, Andreea Anghel, Haralampos Pozidis:
Sampling Acquisition Functions for Batch Bayesian Optimization. CoRR abs/1903.09434 (2019) - 2018
- [c1]Lukas Gianinazzi
, Pavel Kalvoda, Alessandro De Palma, Maciej Besta, Torsten Hoefler:
Communication-avoiding parallel minimum cuts and connected components. PPoPP 2018: 219-232 - [i2]Andreea Anghel, Nikolaos Papandreou, Thomas P. Parnell, Alessandro De Palma, Haralampos Pozidis:
Benchmarking and Optimization of Gradient Boosted Decision Tree Algorithms. CoRR abs/1809.04559 (2018) - 2017
- [i1]Alessandro De Palma, Erik Hemberg, Una-May O'Reilly:
Distributed Stratified Locality Sensitive Hashing for Critical Event Prediction in the Cloud. CoRR abs/1712.00206 (2017)
Coauthor Index
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