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Mean Nyström Embeddings for Adaptive Compressive Learning


Oct 21, 2021
Antoine Chatalic, Luigi Carratino, Ernesto De Vito, Lorenzo Rosasco

* 22 pages, 4 figures 

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Understanding neural networks with reproducing kernel Banach spaces


Sep 20, 2021
Francesca Bartolucci, Ernesto De Vito, Lorenzo Rosasco, Stefano Vigogna


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From inexact optimization to learning via gradient concentration


Jun 24, 2021
Bernhard Stankewitz, Nicole Mücke, Lorenzo Rosasco


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ParK: Sound and Efficient Kernel Ridge Regression by Feature Space Partitions


Jun 23, 2021
Luigi Carratino, Stefano Vigogna, Daniele Calandriello, Lorenzo Rosasco


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Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domain by Adaptive Discretization


Jun 16, 2021
Marco Rando, Luigi Carratino, Silvia Villa, Lorenzo Rosasco


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On the Emergence of Whole-body Strategies from Humanoid Robot Push-recovery Learning


Apr 29, 2021
Diego Ferigo, Raffaello Camoriano, Paolo Maria Viceconte, Daniele Calandriello, Silvio Traversaro, Lorenzo Rosasco, Daniele Pucci

* Co-first authors: Diego Ferigo and Raffaello Camoriano; 8 pages 

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Structured Prediction for CRiSP Inverse Kinematics Learning with Misspecified Robot Models


Mar 01, 2021
Gian Maria Marconi, Raffaello Camoriano, Lorenzo Rosasco, Carlo Ciliberto


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Data-efficient Weakly-supervised Learning for On-line Object Detection under Domain Shift in Robotics


Dec 28, 2020
Elisa Maiettini, Raffaello Camoriano, Giulia Pasquale, Vadim Tikhanoff, Lorenzo Rosasco, Lorenzo Natale


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Fast Object Segmentation Learning with Kernel-based Methods for Robotics


Nov 25, 2020
Federico Ceola, Elisa Maiettini, Giulia Pasquale, Lorenzo Rosasco, Lorenzo Natale

* Manuscript submitted to 2021 IEEE International Conference on Robotics and Automation (ICRA) 

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Fast Region Proposal Learning for Object Detection for Robotics


Nov 25, 2020
Federico Ceola, Elisa Maiettini, Giulia Pasquale, Lorenzo Rosasco, Lorenzo Natale

* Preprint submitted to IEEE Robotics and Automation Letters as Submission for RA-L and ICRA 2021 

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Decentralised Learning with Random Features and Distributed Gradient Descent


Jul 01, 2020
Dominic Richards, Patrick Rebeschini, Lorenzo Rosasco


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For interpolating kernel machines, the minimum norm ERM solution is the most stable


Jun 28, 2020
Akshay Rangamani, Lorenzo Rosasco, Tomaso Poggio


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Kernel methods through the roof: handling billions of points efficiently


Jun 18, 2020
Giacomo Meanti, Luigi Carratino, Lorenzo Rosasco, Alessandro Rudi

* 33 pages, 7 figures 

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Regularized ERM on random subspaces


Jun 17, 2020
Andrea Della Vecchia, Jaouad Mourtada, Ernesto De Vito, Lorenzo Rosasco


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Interpolation and Learning with Scale Dependent Kernels


Jun 17, 2020
Nicolò Pagliana, Alessandro Rudi, Ernesto De Vito, Lorenzo Rosasco


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Implicit regularization for convex regularizers


Jun 17, 2020
Cesare Molinari, Mathurin Massias, Lorenzo Rosasco, Silvia Villa


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Asymptotics of Ridge(less) Regression under General Source Condition


Jun 11, 2020
Dominic Richards, Jaouad Mourtada, Lorenzo Rosasco


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Hyperbolic Manifold Regression


May 28, 2020
Gian Maria Marconi, Lorenzo Rosasco, Carlo Ciliberto

* 13 pages, 3 figures To be published in 23rd International Conference on Artificial Intelligence and Statistics Conference Proceedings 

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Constructing fast approximate eigenspaces with application to the fast graph Fourier transforms


Mar 20, 2020
Cristian Rusu, Lorenzo Rosasco


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Near-linear Time Gaussian Process Optimization with Adaptive Batching and Resparsification


Feb 26, 2020
Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco


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A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings


Feb 13, 2020
Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi

* 53 pages 

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Multi-Scale Vector Quantization with Reconstruction Trees


Sep 04, 2019
Enrico Cecini, Ernesto De Vito, Lorenzo Rosasco


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Statistical and Computational Trade-Offs in Kernel K-Means


Aug 27, 2019
Daniele Calandriello, Lorenzo Rosasco

* Advances in Neural Information Processing Systems, pp. 9357-9367. 2018 

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Fast approximation of orthogonal matrices and application to PCA


Jul 18, 2019
Cristian Rusu, Lorenzo Rosasco


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Gain with no Pain: Efficient Kernel-PCA by Nyström Sampling


Jul 11, 2019
Nicholas Sterge, Bharath Sriperumbudur, Lorenzo Rosasco, Alessandro Rudi

* 19 pages, 2 figures 

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