Seuraa
Daniele Calandriello
Daniele Calandriello
Research Scientist, DeepMind
Vahvistettu sähköpostiosoite verkkotunnuksessa google.com
Nimike
Viittaukset
Viittaukset
Vuosi
Safe policy iteration
M Pirotta, M Restelli, A Pecorino, D Calandriello
International Conference on Machine Learning, 307-315, 2013
1112013
On fast leverage score sampling and optimal learning
A Rudi, D Calandriello, L Carratino, L Rosasco
Advances in Neural Information Processing Systems 31, 2018
842018
Sparse multi-task reinforcement learning
D Calandriello, A Lazaric, M Restelli
Advances in neural information processing systems 27, 2014
772014
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
752019
Exact sampling of determinantal point processes with sublinear time preprocessing
M Derezinski, D Calandriello, M Valko
Advances in neural information processing systems 32, 2019
552019
Second-Order Kernel Online Convex Optimization with Adaptive Sketching
D Calandriello, A Lazaric, M Valko
International Conference on Machine Learning, 2017
412017
Distributed adaptive sampling for kernel matrix approximation
D Calandriello, A Lazaric, M Valko
International Conference on Artificial Intelligence and Statistics, 2017
38*2017
Efficient second-order online kernel learning with adaptive embedding
D Calandriello, A Lazaric, M Valko
Advances in Neural Information Processing Systems, 2017
372017
Byol-explore: Exploration by bootstrapped prediction
Z Guo, S Thakoor, M Pîslar, B Avila Pires, F Altché, C Tallec, A Saade, ...
Advances in neural information processing systems 35, 31855-31870, 2022
352022
Physically interactive robogames: Definition and design guidelines
D Martinoia, D Calandriello, A Bonarini
Robotics and Autonomous Systems 61 (8), 739-748, 2013
332013
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
322018
Information-theoretic online memory selection for continual learning
S Sun, D Calandriello, H Hu, A Li, M Titsias
arXiv preprint arXiv:2204.04763, 2022
312022
Statistical and computational trade-offs in kernel k-means
D Calandriello, L Rosasco
Advances in neural information processing systems 31, 2018
302018
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
242020
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
222020
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
172016
Semi-supervised information-maximization clustering
D Calandriello, G Niu, M Sugiyama
Neural networks 57, 103-111, 2014
152014
One pass imagenet
H Hu, A Li, D Calandriello, D Gorur
arXiv preprint arXiv:2111.01956, 2021
132021
Scaling gaussian process optimization by evaluating a few unique candidates multiple times
D Calandriello, L Carratino, A Lazaric, M Valko, L Rosasco
International Conference on Machine Learning, 2523-2541, 2022
122022
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
122018
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Artikkelit 1–20