Articles with public access mandates - Daniele CalandrielloLearn more
Available somewhere: 15
On fast leverage score sampling and optimal learning
A Rudi, D Calandriello, L Carratino, L Rosasco
Advances in Neural Information Processing Systems 31, 2018
Mandates: US National Science Foundation, US Department of Defense, European Commission
Gaussian process optimization with adaptive sketching: Scalable and no regret
D Calandriello, L Carratino, A Lazaric, M Valko, L Rosasco
32nd Annual Conference on Learning Theory, 2019
Mandates: US National Science Foundation, US Department of Defense, European …
Exact sampling of determinantal point processes with sublinear time preprocessing
M Derezinski, D Calandriello, M Valko
Advances in neural information processing systems 32, 2019
Mandates: US National Science Foundation
Improved large-scale graph learning through ridge spectral sparsification
D Calandriello, I Koutis, A Lazaric, M Valko
International Conference on Machine Learning, 687--696, 2018
Mandates: US National Science Foundation
Statistical and computational trade-offs in kernel k-means
D Calandriello, L Rosasco
Advances in neural information processing systems 31, 2018
Mandates: US National Science Foundation, US Department of Defense, European Commission
Sampling from a k-DPP without looking at all items
D Calandriello, M Derezinski, M Valko
Advances in Neural Information Processing Systems 33, 6889-6899, 2020
Mandates: US National Science Foundation
Near-linear time Gaussian process optimization with adaptive batching and resparsification
D Calandriello, L Carratino, A Lazaric, M Valko, L Rosasco
International Conference on Machine Learning, 1295-1305, 2020
Mandates: US National Science Foundation, US Department of Defense, European Commission
Constrained DMPs for feasible skill learning on humanoid robots
A Duan, R Camoriano, D Ferigo, D Calandriello, L Rosasco, D Pucci
2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids), 1-6, 2018
Mandates: US National Science Foundation, US Department of Defense, European Commission
On the emergence of whole-body strategies from humanoid robot push-recovery learning
D Ferigo, R Camoriano, PM Viceconte, D Calandriello, S Traversaro, ...
IEEE Robotics and Automation Letters 6 (4), 8561-8568, 2021
Mandates: US National Science Foundation, US Department of Defense, European Commission
Fast rates for maximum entropy exploration
D Tiapkin, D Belomestny, D Calandriello, E Moulines, R Munos, ...
International Conference on Machine Learning, 34161-34221, 2023
Mandates: German Research Foundation, Agence Nationale de la Recherche
Learning to avoid obstacles with minimal intervention control
A Duan, R Camoriano, D Ferigo, Y Huang, D Calandriello, L Rosasco, ...
Frontiers in Robotics and AI 7, 60, 2020
Mandates: US National Science Foundation, US Department of Defense, European Commission
Park: Sound and efficient kernel ridge regression by feature space partitions
L Carratino, S Vigogna, D Calandriello, L Rosasco
Advances in Neural Information Processing Systems 34, 6430-6441, 2021
Mandates: US National Science Foundation, US Department of Defense, European Commission
Optimistic posterior sampling for reinforcement learning with few samples and tight guarantees
D Tiapkin, D Belomestny, D Calandriello, É Moulines, R Munos, ...
Advances in Neural Information Processing Systems 35, 10737-10751, 2022
Mandates: German Research Foundation, Agence Nationale de la Recherche
Learning to sequence multiple tasks with competing constraints
A Duan, R Camoriano, D Ferigo, Y Huang, D Calandriello, L Rosasco, ...
2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019
Mandates: US National Science Foundation
Model-free posterior sampling via learning rate randomization
D Tiapkin, D Belomestny, D Calandriello, E Moulines, R Munos, ...
Advances in Neural Information Processing Systems 36, 2024
Mandates: Agence Nationale de la Recherche
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