NIPS Proceedings
^{β}
Books
Lorenzo Rosasco
20 Papers
Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification
(2018)
Learning with SGD and Random Features
(2018)
Manifold Structured Prediction
(2018)
On Fast Leverage Score Sampling and Optimal Learning
(2018)
Statistical and Computational Trade-Offs in Kernel K-Means
(2018)
Consistent Multitask Learning with Nonlinear Output Relations
(2017)
FALKON: An Optimal Large Scale Kernel Method
(2017)
Generalization Properties of Learning with Random Features
(2017)
A Consistent Regularization Approach for Structured Prediction
(2016)
Optimal Learning for Multi-pass Stochastic Gradient Methods
(2016)
Learning with Incremental Iterative Regularization
(2015)
Less is More: Nyström Computational Regularization
(2015)
On the Sample Complexity of Subspace Learning
(2013)
Learning Manifolds with K-Means and K-Flats
(2012)
Learning Probability Measures with respect to Optimal Transport Metrics
(2012)
Multiclass Learning with Simplex Coding
(2012)
A Primal-Dual Algorithm for Group Sparse Regularization with Overlapping Groups
(2010)
Spectral Regularization for Support Estimation
(2010)
On Invariance in Hierarchical Models
(2009)
Learning, Regularization and Ill-Posed Inverse Problems
(2004)