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Daniele Calandriello
Daniele Calandriello
Research Scientist, DeepMind
Verified email at google.com
Title
Cited by
Cited by
Year
Safe policy iteration
M Pirotta, M Restelli, A Pecorino, D Calandriello
International Conference on Machine Learning, 307-315, 2013
872013
Sparse multi-task reinforcement learning
D Calandriello, A Lazaric, M Restelli
Advances in neural information processing systems 27, 2014
582014
On fast leverage score sampling and optimal learning
A Rudi, D Calandriello, L Carratino, L Rosasco
Advances in Neural Information Processing Systems 31, 2018
542018
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
492019
Exact sampling of determinantal point processes with sublinear time preprocessing
M Derezinski, D Calandriello, M Valko
Advances in neural information processing systems 32, 2019
342019
Physically interactive robogames: Definition and design guidelines
D Martinoia, D Calandriello, A Bonarini
Robotics and Autonomous Systems 61 (8), 739-748, 2013
322013
Second-Order Kernel Online Convex Optimization with Adaptive Sketching
D Calandriello, A Lazaric, M Valko
International Conference on Machine Learning, 2017
302017
Efficient second-order online kernel learning with adaptive embedding
D Calandriello, A Lazaric, M Valko
Advances in Neural Information Processing Systems, 2017
272017
Distributed adaptive sampling for kernel matrix approximation
D Calandriello, A Lazaric, M Valko
International Conference on Artificial Intelligence and Statistics, 2017
26*2017
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
172018
Analysis of Nystr÷m method with sequential ridge leverage score sampling
D Calandriello, A Lazaric, M Valko
Proceedings of the Thirty-Second Conference on Uncertainty in Artificialá…, 2016
152016
Statistical and computational trade-offs in kernel k-means
D Calandriello, L Rosasco
Advances in neural information processing systems 31, 2018
142018
Semi-supervised information-maximization clustering
D Calandriello, G Niu, M Sugiyama
Neural networks 57, 103-111, 2014
122014
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
112020
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
102020
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
72018
Efficient Sequential Learning in Structured and Constrained Environments
D Calandriello
Inria Lille Nord Europe-Laboratoire CRIStAL-UniversitÚ de Lille, 2017
52017
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
32020
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 Systemsá…, 2019
32019
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, 2021
22021
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