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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
1002013
On fast leverage score sampling and optimal learning
A Rudi, D Calandriello, L Carratino, L Rosasco
Advances in Neural Information Processing Systems 31, 2018
662018
Sparse multi-task reinforcement learning
D Calandriello, A Lazaric, M Restelli
Advances in neural information processing systems 27, 2014
612014
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
592019
Exact sampling of determinantal point processes with sublinear time preprocessing
M Derezinski, D Calandriello, M Valko
Advances in neural information processing systems 32, 2019
432019
Second-Order Kernel Online Convex Optimization with Adaptive Sketching
D Calandriello, A Lazaric, M Valko
International Conference on Machine Learning, 2017
332017
Distributed adaptive sampling for kernel matrix approximation
D Calandriello, A Lazaric, M Valko
International Conference on Artificial Intelligence and Statistics, 2017
33*2017
Physically interactive robogames: Definition and design guidelines
D Martinoia, D Calandriello, A Bonarini
Robotics and Autonomous Systems 61 (8), 739-748, 2013
322013
Efficient second-order online kernel learning with adaptive embedding
D Calandriello, A Lazaric, M Valko
Advances in Neural Information Processing Systems, 2017
292017
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
252018
Statistical and computational trade-offs in kernel k-means
D Calandriello, L Rosasco
Advances in neural information processing systems 31, 2018
222018
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
162020
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
152020
Analysis of Nyström method with sequential ridge leverage score sampling
D Calandriello, A Lazaric, M Valko
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial …, 2016
152016
Semi-supervised information-maximization clustering
D Calandriello, G Niu, M Sugiyama
Neural Networks 57, 103-111, 2014
142014
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
92018
Information-theoretic online memory selection for continual learning
S Sun, D Calandriello, H Hu, A Li, M Titsias
arXiv preprint arXiv:2204.04763, 2022
82022
Byol-explore: Exploration by bootstrapped prediction
ZD Guo, S Thakoor, M Pîslar, BA Pires, F Altché, C Tallec, A Saade, ...
arXiv preprint arXiv:2206.08332, 2022
52022
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
52019
Efficient Sequential Learning in Structured and Constrained Environments
D Calandriello
Inria Lille Nord Europe-Laboratoire CRIStAL-Université de Lille, 2017
52017
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