Daniele Calandriello
Daniele Calandriello
PostDoc, LCSL
Verified email at iit.it - Homepage
TitleCited byYear
Safe policy iteration
M Pirotta, M Restelli, A Pecorino, D Calandriello
International Conference on Machine Learning, 307-315, 2013
402013
Physically interactive robogames: Definition and design guidelines
D Martinoia, D Calandriello, A Bonarini
Robotics and Autonomous Systems 61 (8), 739-748, 2013
242013
Sparse multi-task reinforcement learning
D Calandriello, A Lazaric, M Restelli
Advances in Neural Information Processing Systems, 819-827, 2014
192014
On fast leverage score sampling and optimal learning
A Rudi, D Calandriello, L Carratino, L Rosasco
Advances in Neural Information Processing Systems, 5672-5682, 2018
152018
Distributed adaptive sampling for kernel matrix approximation
D Calandriello, A Lazaric, M Valko
International Conference on Artificial Intelligence and Statistics, 2017
15*2017
Second-Order Kernel Online Convex Optimization with Adaptive Sketching
D Calandriello, A Lazaric, M Valko
International Conference on Machine Learning, 2017
142017
Efficient second-order online kernel learning with adaptive embedding
D Calandriello, A Lazaric, M Valko
Advances in Neural Information Processing Systems, 2017
112017
Analysis of Nyström method with sequential ridge leverage score sampling
D Calandriello, A Lazaric, M Valko
102016
Semi-supervised information-maximization clustering
D Calandriello, G Niu, M Sugiyama
Neural Networks 57, 103-111, 2014
82014
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
42018
Exact sampling of determinantal point processes with sublinear time preprocessing
M Dereziński, D Calandriello, M Valko
arXiv preprint arXiv:1905.13476, 2019
32019
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
22019
Efficient Sequential Learning in Structured and Constrained Environments
D Calandriello
22017
Pack only the essentials: Adaptive dictionary learning for kernel ridge regression
D Calandriello, A Lazaric, M Valko
22016
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
12018
Statistical and computational trade-offs in kernel k-means
D Calandriello, L Rosasco
Advances in Neural Information Processing Systems, 9357-9367, 2018
12018
Analysis of kelner and levin graph sparsification algorithm for a streaming setting
D Calandriello, A Lazaric, M Valko
arXiv preprint arXiv:1609.03769, 2016
12016
Incremental spectral sparsification for large-scale graph-based semi-supervised learning
D Calandriello, A Lazaric, M Valko, I Koutis
arXiv preprint arXiv:1601.05675, 2016
12016
Large-scale semi-supervised learning with online spectral graph sparsification
D Calandriello, A Lazaric, M Valko
12015
Learning to Sequence Multiple Tasks with Competing Constraints
A Duan, R Camoriano, D Ferigo, Y Huang, D Calandriello, L Rosasco, ...
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