Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström method - Edoardo Caldarelli; Antoine Chatalic; Adrià Colomé; Cesare Molinari; Carlos Ocampo-Martinez; Carme Torras; Lorenzo Rosasco (Autom., 2025)

Learning Rhythmic Trajectories With Geometric Constraints for Laser-Based Skincare Procedures - Anqing Duan; Wanli Liuchen; Jinsong Wu; Raffaello Camoriano; Lorenzo Rosasco; David Navarro-Alarcon (IEEE Trans. Robotics, 2025)

Towards a learning theory of representation alignment - Francesco Insulla; Shuo Huang; Lorenzo Rosasco (The Thirteenth International Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025, 2025)

Learning convolution operators on compact Abelian groups - Emilia Magnani; Ernesto De Vito; Philipp Hennig; Lorenzo Rosasco (CoRR, 2025)

Re-examining Double Descent and Scaling Laws under Norm-based Capacity via Deterministic Equivalence - Yichen Wang; Yudong Chen; Lorenzo Rosasco; Fanghui Liu (CoRR, 2025)

An Efficient Permutation-Based Kernel Two-Sample Test - Antoine Chatalic; Marco Letizia; Nicolas Schreuder; Lorenzo Rosasco (CoRR, 2025)

Towards a Learning Theory of Representation Alignment - Francesco Insulla; Shuo Huang; Lorenzo Rosasco (CoRR, 2025)

Computational Efficiency under Covariate Shift in Kernel Ridge Regression - Andrea Della Vecchia; Arnaud Mavakala Watusadisi; Ernesto De Vito; Lorenzo Rosasco (CoRR, 2025)

A Structured Tour of Optimization with Finite Differences - Marco Rando; Cesare Molinari; Lorenzo Rosasco; Silvia Villa (CoRR, 2025)

Stochastic zeroth order descent with structured directions - Marco Rando; Cesare Molinari; Silvia Villa; Lorenzo Rosasco (Comput. Optim. Appl., 2024)

A structured prediction approach for robot imitation learning - Anqing Duan; Iason Batzianoulis; Raffaello Camoriano; Lorenzo Rosasco; Daniele Pucci; Aude Billard (Int. J. Robotics Res., 2024)

Top-tuning: A study on transfer learning for an efficient alternative to fine tuning for image classification with fast kernel methods - Paolo Didier Alfano; Vito Paolo Pastore; Lorenzo Rosasco; Francesca Odone (Image Vis. Comput., 2024)

Iterative regularization for low complexity regularizers - Cesare Molinari; Mathurin Massias; Lorenzo Rosasco; Silvia Villa (Numerische Mathematik, 2024)

RESPRECT: Speeding-up Multi-Fingered Grasping With Residual Reinforcement Learning - Federico Ceola; Lorenzo Rosasco; Lorenzo Natale (IEEE Robotics Autom. Lett., 2024)

Automatic Gain Tuning for Humanoid Robots Walking Architectures Using Gradient-Free Optimization Techniques - Carlotta Sartore; Marco Rando; Giulio Romualdi; Cesare Molinari; Lorenzo Rosasco; Daniele Pucci (23rd IEEE-RAS International Conference on Humanoid Robots, Humanoids 2024, Nancy, France, November 22-24, 2024, 2024)

Sim2Real Bilevel Adaptation for Object Surface Classification using Vision-Based Tactile Sensors - Gabriele M. Caddeo; Andrea Maracani; Paolo Didier Alfano; Nicola A. Piga; Lorenzo Rosasco; Lorenzo Natale (IEEE International Conference on Robotics and Automation, ICRA 2024, Yokohama, Japan, May 13-17, 2024, 2024)

RESPRECT: Speeding-up Multi-fingered Grasping with Residual Reinforcement Learning - Federico Ceola; Lorenzo Rosasco; Lorenzo Natale (CoRR, 2024)

Key Design Choices in Source-Free Unsupervised Domain Adaptation: An In-depth Empirical Analysis - Andrea Maracani; Raffaello Camoriano; Elisa Maiettini; Davide Talon; Lorenzo Rosasco; Lorenzo Natale (CoRR, 2024)

Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström method - Edoardo Caldarelli; Antoine Chatalic; Adrià Colomé; Cesare Molinari; Carlos Ocampo-Martinez; Carme Torras; Lorenzo Rosasco (CoRR, 2024)

Neural reproducing kernel Banach spaces and representer theorems for deep networks - Francesca Bartolucci; Ernesto De Vito; Lorenzo Rosasco; Stefano Vigogna (CoRR, 2024)

Q-Learning to navigate turbulence without a map - Marco Rando; Martin James; Alessandro Verri; Lorenzo Rosasco; Agnese Seminara (CoRR, 2024)

A New Formulation for Zeroth-Order Optimization of Adversarial EXEmples in Malware Detection - Marco Rando; Luca Demetrio; Lorenzo Rosasco; Fabio Roli (CoRR, 2024)

Trust And Balance: Few Trusted Samples Pseudo-Labeling and Temperature Scaled Loss for Effective Source-Free Unsupervised Domain Adaptation - Andrea Maracani; Lorenzo Rosasco; Lorenzo Natale (CoRR, 2024)

Automatic Gain Tuning for Humanoid Robots Walking Architectures Using Gradient-Free Optimization Techniques - Carlotta Sartore; Marco Rando; Giulio Romualdi; Cesare Molinari; Lorenzo Rosasco; Daniele Pucci (CoRR, 2024)

Optimization Insights into Deep Diagonal Linear Networks - Hippolyte Labarrière; Cesare Molinari; Lorenzo Rosasco; Silvia Villa; Cristian Vega (CoRR, 2024)

From inexact optimization to learning via gradient concentration - Bernhard Stankewitz; Nicole Mücke; Lorenzo Rosasco (Comput. Optim. Appl., 2023)

Fast kernel methods for data quality monitoring as a goodness-of-fit test - Gaia Grosso; Nicolò Lai; Marco Letizia; Jacopo Pazzini; Marco Rando; Lorenzo Rosasco; Andrea Wulzer; Marco Zanetti (Mach. Learn. Sci. Technol., 2023)

Convergence of the forward-backward algorithm: beyond the worst-case with the help of geometry - Guillaume Garrigos; Lorenzo Rosasco; Silvia Villa (Math. Program., 2023)

Zeroth-order optimization with orthogonal random directions - David Kozak; Cesare Molinari; Lorenzo Rosasco; Luis Tenorio; Silvia Villa (Math. Program., 2023)

Causal Discovery with Score Matching on Additive Models with Arbitrary Noise - Francesco Montagna; Nicoletta Noceti; Lorenzo Rosasco; Kun Zhang; Francesco Locatello (Conference on Causal Learning and Reasoning, CLeaR 2023, 11-14 April 2023, Amazon Development Center, Tübingen, Germany, April 11-14, 2023, 2023)

Scalable Causal Discovery with Score Matching - Francesco Montagna; Nicoletta Noceti; Lorenzo Rosasco; Kun Zhang; Francesco Locatello (Conference on Causal Learning and Reasoning, CLeaR 2023, 11-14 April 2023, Amazon Development Center, Tübingen, Germany, April 11-14, 2023, 2023)

Heteroscedastic Gaussian Processes and Random Features: Scalable Motion Primitives with Guarantees - Edoardo Caldarelli; Antoine Chatalic; Adrià Colomé; Lorenzo Rosasco; Carme Torras (Conference on Robot Learning, CoRL 2023, 6-9 November 2023, Atlanta, GA, USA, 2023)

Regularization Properties of Dual Subgradient Flow - Vassilis Apidopoulos; Cesare Molinari; Lorenzo Rosasco; Silvia Villa (European Control Conference, ECC 2023, Bucharest, Romania, June 13-16, 2023, 2023)

A Grasp Pose is All You Need: Learning Multi-Fingered Grasping with Deep Reinforcement Learning from Vision and Touch - Federico Ceola; Elisa Maiettini; Lorenzo Rosasco; Lorenzo Natale (IROS, 2023)

Estimating Koopman operators with sketching to provably learn large scale dynamical systems - Giacomo Meanti; Antoine Chatalic; Vladimir Kostic; Pietro Novelli; Massimiliano Pontil; Lorenzo Rosasco (Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023)

Assumption violations in causal discovery and the robustness of score matching - Francesco Montagna; Atalanti-Anastasia Mastakouri; Elias Eulig; Nicoletta Noceti; Lorenzo Rosasco; Dominik Janzing; Bryon Aragam; Francesco Locatello (Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023)

An Optimal Structured Zeroth-order Algorithm for Non-smooth Optimization - Marco Rando; Cesare Molinari; Lorenzo Rosasco; Silvia Villa (Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023)

The Thirty Sixth Annual Conference on Learning Theory, COLT 2023, 12-15 July 2023, Bangalore, India - Gergely Neu; Lorenzo Rosasco (PMLR, 2023)

Key Design Choices for Double-Transfer in Source-Free Unsupervised Domain Adaptation - Andrea Maracani; Raffaello Camoriano; Elisa Maiettini; Davide Talon; Lorenzo Rosasco; Lorenzo Natale (CoRR, 2023)

Fast kernel methods for Data Quality Monitoring as a goodness-of-fit test - Gaia Grosso; Nicolò Lai; Marco Letizia; Jacopo Pazzini; Marco Rando; Lorenzo Rosasco; Andrea Wulzer; Marco Zanetti (CoRR, 2023)

Causal Discovery with Score Matching on Additive Models with Arbitrary Noise - Francesco Montagna; Nicoletta Noceti; Lorenzo Rosasco; Kun Zhang; Francesco Locatello (CoRR, 2023)

Scalable Causal Discovery with Score Matching - Francesco Montagna; Nicoletta Noceti; Lorenzo Rosasco; Kun Zhang; Francesco Locatello (CoRR, 2023)

A Grasp Pose is All You Need: Learning Multi-fingered Grasping with Deep Reinforcement Learning from Vision and Touch - Federico Ceola; Elisa Maiettini; Lorenzo Rosasco; Lorenzo Natale (CoRR, 2023)

Estimating Koopman operators with sketching to provably learn large scale dynamical systems - Giacomo Meanti; Antoine Chatalic; Vladimir R. Kostic; Pietro Novelli; Massimiliano Pontil; Lorenzo Rosasco (CoRR, 2023)

A Structured Prediction Approach for Robot Imitation Learning - Anqing Duan; Iason Batzianoulis; Raffaello Camoriano; Lorenzo Rosasco; Daniele Pucci; Aude Billard (CoRR, 2023)

Assumption violations in causal discovery and the robustness of score matching - Francesco Montagna; Atalanti-Anastasia Mastakouri; Elias Eulig; Nicoletta Noceti; Lorenzo Rosasco; Dominik Janzing; Bryon Aragam; Francesco Locatello (CoRR, 2023)

Shortcuts for causal discovery of nonlinear models by score matching - Francesco Montagna; Nicoletta Noceti; Lorenzo Rosasco; Francesco Locatello (CoRR, 2023)

Sim2Real Bilevel Adaptation for Object Surface Classification using Vision-Based Tactile Sensors - Gabriele M. Caddeo; Andrea Maracani; Paolo Didier Alfano; Nicola A. Piga; Lorenzo Rosasco; Lorenzo Natale (CoRR, 2023)

Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling - Antoine Chatalic; Nicolas Schreuder; Ernesto De Vito; Lorenzo Rosasco (CoRR, 2023)

Learning Rhythmic Trajectories with Geometric Constraints for Laser-Based Skincare Procedures - Anqing Duan; Wanli Liuchen; Jinsong Wu; Raffaello Camoriano; Lorenzo Rosasco; David Navarro-Alarcon (CoRR, 2023)

ADHERENT: Learning Human-like Trajectory Generators for Whole-body Control of Humanoid Robots - Paolo Maria Viceconte; Raffaello Camoriano; Giulio Romualdi; Diego Ferigo; Stefano Dafarra; Silvio Traversaro; Giuseppe Oriolo; Lorenzo Rosasco; Daniele Pucci (IEEE Robotics Autom. Lett., 2022)

Fast approximation of orthogonal matrices and application to PCA - Cristian Rusu; Lorenzo Rosasco (Signal Process., 2022)

Learn Fast, Segment Well: Fast Object Segmentation Learning on the iCub Robot - Federico Ceola; Elisa Maiettini; Giulia Pasquale; Giacomo Meanti; Lorenzo Rosasco; Lorenzo Natale (IEEE Trans. Robotics, 2022)

Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression - Giacomo Meanti; Luigi Carratino; Ernesto De Vito; Lorenzo Rosasco (International Conference on Artificial Intelligence and Statistics, AISTATS 2022, 28-30 March 2022, Virtual Event, 2022)

Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domains by Adaptive Discretization - Marco Rando; Luigi Carratino; Silvia Villa; Lorenzo Rosasco (International Conference on Artificial Intelligence and Statistics, AISTATS 2022, 28-30 March 2022, Virtual Event, 2022)

Mean Nyström Embeddings for Adaptive Compressive Learning - Antoine Chatalic; Luigi Carratino; Ernesto De Vito; Lorenzo Rosasco (International Conference on Artificial Intelligence and Statistics, AISTATS 2022, 28-30 March 2022, Virtual Event, 2022)

Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times - Daniele Calandriello; Luigi Carratino; Alessandro Lazaric; Michal Valko; Lorenzo Rosasco (International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA, 2022)

Nyström Kernel Mean Embeddings - Antoine Chatalic; Nicolas Schreuder; Lorenzo Rosasco; Alessandro Rudi (International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA, 2022)

Multiclass learning with margin: exponential rates with no bias-variance trade-off - Stefano Vigogna; Giacomo Meanti; Ernesto De Vito; Lorenzo Rosasco (International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA, 2022)

Efficient Unsupervised Learning for Plankton Images - Paolo Didier Alfano; Marco Rando; Marco Letizia; Francesca Odone; Lorenzo Rosasco; Vito Paolo Pastore (26th International Conference on Pattern Recognition, ICPR 2022, Montreal, QC, Canada, August 21-25, 2022, 2022)

Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces - Vladimir Kostic; Pietro Novelli; Andreas Maurer; Carlo Ciliberto; Lorenzo Rosasco; Massimiliano Pontil (Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022, 2022)

From Handheld to Unconstrained Object Detection: a Weakly-supervised On-line Learning Approach - Elisa Maiettini; Andrea Maracani; Raffaello Camoriano; Giulia Pasquale; Vadim Tikhanoff; Lorenzo Rosasco; Lorenzo Natale (31st IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2022, Napoli, Italy, August 29 - Sept. 2, 2022, 2022)

Dataset associated to the "ADHERENT: Learning Human-like Trajectory Generators for Whole-body Control of Humanoid Robots" paper (manuscript DOI: 10.1109/LRA.2022.3141658) (Version 1) - Paolo Maria Viceconte; Raffaello Camoriano; Giulio Romualdi; Diego Ferigo; Stefano Dafarra; Silvio Traversaro; Giuseppe Oriolo; Lorenzo Rosasco; Daniele Pucci (Zenodo, 2022)
Accessed on YYYY-MM-DD.

Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression - Giacomo Meanti; Luigi Carratino; Ernesto De Vito; Lorenzo Rosasco (CoRR, 2022)

Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times - Daniele Calandriello; Luigi Carratino; Alessandro Lazaric; Michal Valko; Lorenzo Rosasco (CoRR, 2022)

Nyström Kernel Mean Embeddings - Antoine Chatalic; Nicolas Schreuder; Alessandro Rudi; Lorenzo Rosasco (CoRR, 2022)

Multiclass learning with margin: exponential rates with no bias-variance trade-off - Stefano Vigogna; Giacomo Meanti; Ernesto De Vito; Lorenzo Rosasco (CoRR, 2022)

An elementary analysis of ridge regression with random design - Jaouad Mourtada; Lorenzo Rosasco (CoRR, 2022)

Physics Informed Shallow Machine Learning for Wind Speed Prediction - Daniele Lagomarsino-Oneto; Giacomo Meanti; Nicolò Pagliana; Alessandro Verri; Andrea Mazzino; Lorenzo Rosasco; Agnese Seminara (CoRR, 2022)

Learning new physics efficiently with nonparametric methods - Marco Letizia; Gianvito Losapio; Marco Rando; Gaia Grosso; Andrea Wulzer; Maurizio Pierini; Marco Zanetti; Lorenzo Rosasco (CoRR, 2022)

Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces - Vladimir Kostic; Pietro Novelli; Andreas Maurer; Carlo Ciliberto; Lorenzo Rosasco; Massimiliano Pontil (CoRR, 2022)

Stochastic Zeroth order Descent with Structured Directions - Marco Rando; Cesare Molinari; Silvia Villa; Lorenzo Rosasco (CoRR, 2022)

Learn Fast, Segment Well: Fast Object Segmentation Learning on the iCub Robot - Federico Ceola; Elisa Maiettini; Giulia Pasquale; Giacomo Meanti; Lorenzo Rosasco; Lorenzo Natale (CoRR, 2022)

Approximate Bayesian Neural Operators: Uncertainty Quantification for Parametric PDEs - Emilia Magnani; Nicholas Krämer; Runa Eschenhagen; Lorenzo Rosasco; Philipp Hennig (CoRR, 2022)

Efficient Unsupervised Learning for Plankton Images - Paolo Didier Alfano; Marco Rando; Marco Letizia; Francesca Odone; Lorenzo Rosasco; Vito Paolo Pastore (CoRR, 2022)

Fine-tuning or top-tuning? Transfer learning with pretrained features and fast kernel methods - Paolo Didier Alfano; Vito Paolo Pastore; Lorenzo Rosasco; Francesca Odone (CoRR, 2022)

Iterative regularization in classification via hinge loss diagonal descent - Vassilis Apidopoulos; Tomaso A. Poggio; Lorenzo Rosasco; Silvia Villa (CoRR, 2022)

Structured Prediction for CRiSP Inverse Kinematics Learning With Misspecified Robot Models - Gian Maria Marconi; Raffaello Camoriano; Lorenzo Rosasco; Carlo Ciliberto (IEEE Robotics Autom. Lett., 2021)

On the Emergence of Whole-Body Strategies From Humanoid Robot Push-Recovery Learning - Diego Ferigo; Raffaello Camoriano; Paolo Maria Viceconte; Daniele Calandriello; Silvio Traversaro; Lorenzo Rosasco; Daniele Pucci (IEEE Robotics Autom. Lett., 2021)

Accelerated Iterative Regularization via Dual Diagonal Descent - Luca Calatroni; Guillaume Garrigos; Lorenzo Rosasco; Silvia Villa (SIAM J. Optim., 2021)

Constructing Fast Approximate Eigenspaces With Application to the Fast Graph Fourier Transforms - Cristian Rusu; Lorenzo Rosasco (IEEE Trans. Signal Process., 2021)

Iterative regularization for convex regularizers - Cesare Molinari; Mathurin Massias; Lorenzo Rosasco; Silvia Villa (The 24th International Conference on Artificial Intelligence and Statistics, AISTATS 2021, April 13-15, 2021, Virtual Event, 2021)

Asymptotics of Ridge(less) Regression under General Source Condition - Dominic Richards; Jaouad Mourtada; Lorenzo Rosasco (The 24th International Conference on Artificial Intelligence and Statistics, AISTATS 2021, April 13-15, 2021, Virtual Event, 2021)

Regularized ERM on random subspaces - Andrea Della Vecchia; Jaouad Mourtada; Ernesto De Vito; Lorenzo Rosasco (The 24th International Conference on Artificial Intelligence and Statistics, AISTATS 2021, April 13-15, 2021, Virtual Event, 2021)

Fast Object Segmentation Learning with Kernel-based Methods for Robotics - Federico Ceola; Elisa Maiettini; Giulia Pasquale; Lorenzo Rosasco; Lorenzo Natale (IEEE International Conference on Robotics and Automation, ICRA 2021, Xi'an, China, May 30 - June 5, 2021, 2021)

ParK: Sound and Efficient Kernel Ridge Regression by Feature Space Partitions - Luigi Carratino; Stefano Vigogna; Daniele Calandriello; Lorenzo Rosasco (Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, 2021)

Structured Prediction for CRiSP Inverse Kinematics Learning with Misspecified Robot Models - Gian Maria Marconi; Raffaello Camoriano; Lorenzo Rosasco; Carlo Ciliberto (CoRR, 2021)

On the Emergence of Whole-body Strategies from Humanoid Robot Push-recovery Learning - Diego Ferigo; Raffaello Camoriano; Paolo Maria Viceconte; Daniele Calandriello; Silvio Traversaro; Lorenzo Rosasco; Daniele Pucci (CoRR, 2021)

From inexact optimization to learning via gradient concentration - Bernhard Stankewitz; Nicole Mücke; Lorenzo Rosasco (CoRR, 2021)

Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domain by Adaptive Discretization - Marco Rando; Luigi Carratino; Silvia Villa; Lorenzo Rosasco (CoRR, 2021)

ParK: Sound and Efficient Kernel Ridge Regression by Feature Space Partitions - Luigi Carratino; Stefano Vigogna; Daniele Calandriello; Lorenzo Rosasco (CoRR, 2021)

Understanding neural networks with reproducing kernel Banach spaces - Francesca Bartolucci; Ernesto De Vito; Lorenzo Rosasco; Stefano Vigogna (CoRR, 2021)

Mean Nyström Embeddings for Adaptive Compressive Learning - Antoine Chatalic; Luigi Carratino; Ernesto De Vito; Lorenzo Rosasco (CoRR, 2021)

On-line object detection: a robotics challenge - Elisa Maiettini; Giulia Pasquale; Lorenzo Rosasco; Lorenzo Natale (Auton. Robots, 2020)

Learning to Avoid Obstacles With Minimal Intervention Control - Anqing Duan; Raffaello Camoriano; Diego Ferigo; Yanlong Huang; Daniele Calandriello; Lorenzo Rosasco; Daniele Pucci (Frontiers Robotics AI, 2020)

Faster Kriging: Facing High-Dimensional Simulators - Xuefei Lu; Alessandro Rudi; Emanuele Borgonovo; Lorenzo Rosasco (Oper. Res., 2020)

A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings - Carlo Ciliberto; Lorenzo Rosasco; Alessandro Rudi (J. Mach. Learn. Res., 2020)

Hyperbolic Manifold Regression - Gian Maria Marconi; Carlo Ciliberto; Lorenzo Rosasco (The 23rd International Conference on Artificial Intelligence and Statistics, AISTATS 2020, 26-28 August 2020, Online [Palermo, Sicily, Italy], 2020)

Gain with no Pain: Efficiency of Kernel-PCA by Nyström Sampling - Nicholas Sterge; Bharath K. Sriperumbudur; Lorenzo Rosasco; Alessandro Rudi (The 23rd International Conference on Artificial Intelligence and Statistics, AISTATS 2020, 26-28 August 2020, Online [Palermo, Sicily, Italy], 2020)

Near-linear time Gaussian process optimization with adaptive batching and resparsification - Daniele Calandriello; Luigi Carratino; Alessandro Lazaric; Michal Valko; Lorenzo Rosasco (Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event, 2020)

Decentralised Learning with Random Features and Distributed Gradient Descent - Dominic Richards; Patrick Rebeschini; Lorenzo Rosasco (Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event, 2020)

Kernel Methods Through the Roof: Handling Billions of Points Efficiently - Giacomo Meanti; Luigi Carratino; Lorenzo Rosasco; Alessandro Rudi (Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020)

A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings - Carlo Ciliberto; Lorenzo Rosasco; Alessandro Rudi (CoRR, 2020)

Constructing fast approximate eigenspaces with application to the fast graph Fourier transforms - Cristian Rusu; Lorenzo Rosasco (CoRR, 2020)

Near-linear Time Gaussian Process Optimization with Adaptive Batching and Resparsification - Daniele Calandriello; Luigi Carratino; Alessandro Lazaric; Michal Valko; Lorenzo Rosasco (CoRR, 2020)

Hyperbolic Manifold Regression - Gian Maria Marconi; Lorenzo Rosasco; Carlo Ciliberto (CoRR, 2020)

Implicit regularization for convex regularizers - Cesare Molinari; Mathurin Massias; Lorenzo Rosasco; Silvia Villa (CoRR, 2020)

Regularized ERM on random subspaces - Andrea Della Vecchia; Jaouad Mourtada; Ernesto De Vito; Lorenzo Rosasco (CoRR, 2020)

Kernel methods through the roof: handling billions of points efficiently - Giacomo Meanti; Luigi Carratino; Lorenzo Rosasco; Alessandro Rudi (CoRR, 2020)

For interpolating kernel machines, the minimum norm ERM solution is the most stable - Akshay Rangamani; Lorenzo Rosasco; Tomaso A. Poggio (CoRR, 2020)

Decentralised Learning with Random Features and Distributed Gradient Descent - Dominic Richards; Patrick Rebeschini; Lorenzo Rosasco (CoRR, 2020)

Fast Region Proposal Learning for Object Detection for Robotics - Federico Ceola; Elisa Maiettini; Giulia Pasquale; Lorenzo Rosasco; Lorenzo Natale (CoRR, 2020)

Fast Object Segmentation Learning with Kernel-based Methods for Robotics - Federico Ceola; Elisa Maiettini; Giulia Pasquale; Lorenzo Rosasco; Lorenzo Natale (CoRR, 2020)

Data-efficient Weakly-supervised Learning for On-line Object Detection under Domain Shift in Robotics - Elisa Maiettini; Raffaello Camoriano; Giulia Pasquale; Vadim Tikhanoff; Lorenzo Rosasco; Lorenzo Natale (CoRR, 2020)

Symmetry-adapted representation learning - Fabio Anselmi; Georgios Evangelopoulos; Lorenzo Rosasco; Tomaso A. Poggio (Pattern Recognit., 2019)

Are we done with object recognition? The iCub robot's perspective - Giulia Pasquale; Carlo Ciliberto; Francesca Odone; Lorenzo Rosasco; Lorenzo Natale (Robotics Auton. Syst., 2019)

Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret - Daniele Calandriello; Luigi Carratino; Alessandro Lazaric; Michal Valko; Lorenzo Rosasco (Conference on Learning Theory, COLT 2019, 25-28 June 2019, Phoenix, AZ, USA, 2019)

A Weakly Supervised Strategy for Learning Object Detection on a Humanoid Robot - Elisa Maiettini; Giulia Pasquale; Vadim Tikhanoff; Lorenzo Rosasco; Lorenzo Natale (19th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2019, Toronto, ON, Canada, October 15-17, 2019, 2019)

Genuine Personality Recognition from Highly Constrained Face Images - Fabio Anselmi; Nicoletta Noceti; Lorenzo Rosasco; Robert Ward (Image Analysis and Processing - ICIAP 2019 - 20th International Conference, Trento, Italy, September 9-13, 2019, Proceedings, Part I, 2019)

Learning to Sequence Multiple Tasks with Competing Constraints - Anqing Duan; Raffaello Camoriano; Diego Ferigo; Yanlong Huang; Daniele Calandriello; Lorenzo Rosasco; Daniele Pucci (2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019, Macau, SAR, China, November 3-8, 2019, 2019)

Beating SGD Saturation with Tail-Averaging and Minibatching - Nicole Mücke; Gergely Neu; Lorenzo Rosasco (Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, 2019)

Implicit Regularization of Accelerated Methods in Hilbert Spaces - Nicolò Pagliana; Lorenzo Rosasco (Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, 2019)

A computational model for grid maps in neural populations - Fabio Anselmi; Benedetta Franceschiello; Micah M. Murray; Lorenzo Rosasco (CoRR, 2019)

Beating SGD Saturation with Tail-Averaging and Minibatching - Nicole Mücke; Gergely Neu; Lorenzo Rosasco (CoRR, 2019)

Theory III: Dynamics and Generalization in Deep Networks - Andrzej Banburski; Qianli Liao; Brando Miranda; Lorenzo Rosasco; Bob Liang; Jack Hidary; Tomaso A. Poggio (CoRR, 2019)

Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret - Daniele Calandriello; Luigi Carratino; Alessandro Lazaric; Michal Valko; Lorenzo Rosasco (CoRR, 2019)

Reproducing kernel Hilbert spaces on manifolds: Sobolev and Diffusion spaces - Ernesto De Vito; Nicole Mücke; Lorenzo Rosasco (CoRR, 2019)

Implicit Regularization of Accelerated Methods in Hilbert Spaces - Nicolò Pagliana; Lorenzo Rosasco (CoRR, 2019)

Multi-Scale Vector Quantization with Reconstruction Trees - Enrico Cecini; Ernesto De Vito; Lorenzo Rosasco (CoRR, 2019)

Gain with no Pain: Efficient Kernel-PCA by Nyström Sampling - Nicholas Sterge; Bharath K. Sriperumbudur; Lorenzo Rosasco; Alessandro Rudi (CoRR, 2019)

Fast approximation of orthogonal matrices and application to PCA - Cristian Rusu; Lorenzo Rosasco (CoRR, 2019)

Statistical and Computational Trade-Offs in Kernel K-Means - Daniele Calandriello; Lorenzo Rosasco (CoRR, 2019)

Modified Fejér sequences and applications - Junhong Lin; Lorenzo Rosasco; Silvia Villa; Ding-Xuan Zhou (Comput. Optim. Appl., 2018)

Generalization properties of doubly stochastic learning algorithms - Junhong Lin; Lorenzo Rosasco (J. Complex., 2018)

Iterative Regularization via Dual Diagonal Descent - Guillaume Garrigos; Lorenzo Rosasco; Silvia Villa (J. Math. Imaging Vis., 2018)

Solving lp-norm regularization with tensor kernels - Saverio Salzo; Lorenzo Rosasco; Johan A. K. Suykens (International Conference on Artificial Intelligence and Statistics, AISTATS 2018, 9-11 April 2018, Playa Blanca, Lanzarote, Canary Islands, Spain, 2018)

Iterate Averaging as Regularization for Stochastic Gradient Descent - Gergely Neu; Lorenzo Rosasco (Conference On Learning Theory, COLT 2018, Stockholm, Sweden, 6-9 July 2018, 2018)

Sparse Multiple Kernel Learning: Support Identification via Mirror Stratifiability - Guillaume Garrigos; Lorenzo Rosasco; Silvia Villa (26th European Signal Processing Conference, EUSIPCO 2018, Roma, Italy, September 3-7, 2018, 2018)

Constrained DMPs for Feasible Skill Learning on Humanoid Robots - Anqing Duan; Raffaello Camoriano; Diego Ferigo; Daniele Calandriello; Lorenzo Rosasco; Daniele Pucci (18th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2018, Beijing, China, November 6-9, 2018, 2018)

Speeding-Up Object Detection Training for Robotics with FALKON - Elisa Maiettini; Giulia Pasquale; Lorenzo Rosasco; Lorenzo Natale (2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018, Madrid, Spain, October 1-5, 2018, 2018)

Manifold Structured Prediction - Alessandro Rudi; Carlo Ciliberto; Gian Maria Marconi; Lorenzo Rosasco (Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada, 2018)

On Fast Leverage Score Sampling and Optimal Learning - Alessandro Rudi; Daniele Calandriello; Luigi Carratino; Lorenzo Rosasco (Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada, 2018)

Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification - Dimitrios Milios; Raffaello Camoriano; Pietro Michiardi; Lorenzo Rosasco; Maurizio Filippone (Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada, 2018)

Statistical and Computational Trade-Offs in Kernel K-Means - Daniele Calandriello; Lorenzo Rosasco (Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada, 2018)

Learning with SGD and Random Features - Luigi Carratino; Alessandro Rudi; Lorenzo Rosasco (Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada, 2018)

Theory of Deep Learning III: explaining the non-overfitting puzzle - Tomaso A. Poggio; Kenji Kawaguchi; Qianli Liao; Brando Miranda; Lorenzo Rosasco; Xavier Boix; Jack Hidary; Hrushikesh N. Mhaskar (CoRR, 2018)

Iterate averaging as regularization for stochastic gradient descent - Gergely Neu; Lorenzo Rosasco (CoRR, 2018)

Speeding-up Object Detection Training for Robotics with FALKON - Elisa Maiettini; Giulia Pasquale; Lorenzo Rosasco; Lorenzo Natale (CoRR, 2018)

Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification - Dimitrios Milios; Raffaello Camoriano; Pietro Michiardi; Lorenzo Rosasco; Maurizio Filippone (CoRR, 2018)

Manifold Structured Prediction - Alessandro Rudi; Carlo Ciliberto; Gian Maria Marconi; Lorenzo Rosasco (CoRR, 2018)

Learning with SGD and Random Features - Luigi Carratino; Alessandro Rudi; Lorenzo Rosasco (CoRR, 2018)

On Fast Leverage Score Sampling and Optimal Learning - Alessandro Rudi; Daniele Calandriello; Luigi Carratino; Lorenzo Rosasco (CoRR, 2018)

Why and when can deep-but not shallow-networks avoid the curse of dimensionality: A review - Tomaso A. Poggio; Hrushikesh N. Mhaskar; Lorenzo Rosasco; Brando Miranda; Qianli Liao (Int. J. Autom. Comput., 2017)

Optimal Rates for Multi-pass Stochastic Gradient Methods - Junhong Lin; Lorenzo Rosasco (J. Mach. Learn. Res., 2017)

Interactive data collection for deep learning object detectors on humanoid robots - Elisa Maiettini; Giulia Pasquale; Lorenzo Rosasco; Lorenzo Natale (17th IEEE-RAS International Conference on Humanoid Robotics, Humanoids 2017, Birmingham, United Kingdom, November 15-17, 2017, 2017)

Incremental robot learning of new objects with fixed update time - Raffaello Camoriano; Giulia Pasquale; Carlo Ciliberto; Lorenzo Natale; Lorenzo Rosasco; Giorgio Metta (2017 IEEE International Conference on Robotics and Automation, ICRA 2017, Singapore, Singapore, May 29 - June 3, 2017, 2017)

Consistent Multitask Learning with Nonlinear Output Relations - Carlo Ciliberto; Alessandro Rudi; Lorenzo Rosasco; Massimiliano Pontil (Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA, 2017)

Generalization Properties of Learning with Random Features - Alessandro Rudi; Lorenzo Rosasco (Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA, 2017)

FALKON: An Optimal Large Scale Kernel Method - Alessandro Rudi; Luigi Carratino; Lorenzo Rosasco (Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA, 2017)

Consistent Multitask Learning with Nonlinear Output Relations - Carlo Ciliberto; Alessandro Rudi; Lorenzo Rosasco; Massimiliano Pontil (CoRR, 2017)

FALKON: An Optimal Large Scale Kernel Method - Alessandro Rudi; Luigi Carratino; Lorenzo Rosasco (CoRR, 2017)

Generalization Properties of Doubly Online Learning Algorithms - Junhong Lin; Lorenzo Rosasco (CoRR, 2017)

Don't relax: early stopping for convex regularization - Simon Matet; Lorenzo Rosasco; Silvia Villa; Bang Long Vu (CoRR, 2017)

Are we Done with Object Recognition? The iCub robot's Perspective - Giulia Pasquale; Carlo Ciliberto; Francesca Odone; Lorenzo Rosasco; Lorenzo Natale (CoRR, 2017)

Optimal Rates for Learning with Nyström Stochastic Gradient Methods - Junhong Lin; Lorenzo Rosasco (CoRR, 2017)

Enabling Depth-Driven Visual Attention on the iCub Humanoid Robot: Instructions for Use and New Perspectives - Giulia Pasquale; Tanis Mar; Carlo Ciliberto; Lorenzo Rosasco; Lorenzo Natale (Frontiers Robotics AI, 2016)

Iterative Regularization for Learning with Convex Loss Functions - Junhong Lin; Lorenzo Rosasco; Ding-Xuan Zhou (J. Mach. Learn. Res., 2016)

Stochastic Forward-Backward Splitting for Monotone Inclusions - Lorenzo Rosasco; Silvia Villa; Bang Công Vu (J. Optim. Theory Appl., 2016)

Unsupervised learning of invariant representations - Fabio Anselmi; Joel Z. Leibo; Lorenzo Rosasco; Jim Mutch; Andrea Tacchetti; Tomaso A. Poggio (Theor. Comput. Sci., 2016)

Holographic Embeddings of Knowledge Graphs - Maximilian Nickel; Lorenzo Rosasco; Tomaso A. Poggio (Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, February 12-17, 2016, Phoenix, Arizona, USA, 2016)

NYTRO: When Subsampling Meets Early Stopping - Raffaello Camoriano; Tomás Angles; Alessandro Rudi; Lorenzo Rosasco (Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, AISTATS 2016, Cadiz, Spain, May 9-11, 2016, 2016)

Combining sensory modalities and exploratory procedures to improve haptic object recognition in robotics - Bertrand Higy; Carlo Ciliberto; Lorenzo Rosasco; Lorenzo Natale (16th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2016, Cancun, Mexico, November 15-17, 2016, 2016)

Active perception: Building objects' models using tactile exploration - Nawid Jamali; Carlo Ciliberto; Lorenzo Rosasco; Lorenzo Natale (16th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2016, Cancun, Mexico, November 15-17, 2016, 2016)

Generalization Properties and Implicit Regularization for Multiple Passes SGM - Junhong Lin; Raffaello Camoriano; Lorenzo Rosasco (Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016, 2016)

Incremental semiparametric inverse dynamics learning - Raffaello Camoriano; Silvio Traversaro; Lorenzo Rosasco; Giorgio Metta; Francesco Nori (2016 IEEE International Conference on Robotics and Automation, ICRA 2016, Stockholm, Sweden, May 16-21, 2016, 2016)

Object identification from few examples by improving the invariance of a Deep Convolutional Neural Network - Giulia Pasquale; Carlo Ciliberto; Lorenzo Rosasco; Lorenzo Natale (2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016, Daejeon, South Korea, October 9-14, 2016, 2016)

A Consistent Regularization Approach for Structured Prediction - Carlo Ciliberto; Lorenzo Rosasco; Alessandro Rudi (Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain, 2016)

Optimal Learning for Multi-pass Stochastic Gradient Methods - Junhong Lin; Lorenzo Rosasco (Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain, 2016)

Incremental Semiparametric Inverse Dynamics Learning - Raffaello Camoriano; Silvio Traversaro; Lorenzo Rosasco; Giorgio Metta; Francesco Nori (CoRR, 2016)

Generalization Properties of Learning with Random Features - Alessandro Rudi; Raffaello Camoriano; Lorenzo Rosasco (CoRR, 2016)

Incremental Object Recognition in Robotics with Extension to New Classes in Constant Time - Raffaello Camoriano; Giulia Pasquale; Carlo Ciliberto; Lorenzo Natale; Lorenzo Rosasco; Giorgio Metta (CoRR, 2016)

A Consistent Regularization Approach for Structured Prediction - Carlo Ciliberto; Alessandro Rudi; Lorenzo Rosasco (CoRR, 2016)

Generalization Properties and Implicit Regularization for Multiple Passes SGM - Junhong Lin; Raffaello Camoriano; Lorenzo Rosasco (CoRR, 2016)

Optimal Learning for Multi-pass Stochastic Gradient Methods - Junhong Lin; Lorenzo Rosasco (CoRR, 2016)

Why and When Can Deep - but Not Shallow - Networks Avoid the Curse of Dimensionality: a Review - Tomaso A. Poggio; Hrushikesh N. Mhaskar; Lorenzo Rosasco; Brando Miranda; Qianli Liao (CoRR, 2016)

Characterizing the Input-Output Function of the Olfactory-Limbic Pathway in the Guinea Pig - Gian Luca Breschi; Carlo Ciliberto; Thierry Nieus; Lorenzo Rosasco; Stefano Taverna; Michela Chiappalone; Valentina Pasquale (Comput. Intell. Neurosci., 2015)

Learning multiple visual tasks while discovering their structure - Carlo Ciliberto; Lorenzo Rosasco; Silvia Villa (IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015, Boston, MA, USA, June 7-12, 2015, 2015)

Teaching iCub to recognize objects using deep Convolutional Neural Networks - Giulia Pasquale; Carlo Ciliberto; Francesca Odone; Lorenzo Rosasco; Lorenzo Natale (Proceedings of the 4th Workshop on Machine Learning for Interactive Systems, MLIS 2015, co-located with the 32nd International Conference on Machine Learning (ICML 2015), Lille, France, July 11th, 2015, 2015)

Convex Learning of Multiple Tasks and their Structure - Carlo Ciliberto; Youssef Mroueh; Tomaso A. Poggio; Lorenzo Rosasco (Proceedings of the 32nd International Conference on Machine Learning, ICML 2015, Lille, France, 6-11 July 2015, 2015)

Discovering discrete subword units with binarized autoencoders and hidden-Markov-model encoders - Leonardo Badino; Alessio Mereta; Lorenzo Rosasco (16th Annual Conference of the International Speech Communication Association, INTERSPEECH 2015, Dresden, Germany, September 6-10, 2015, 2015)

Discriminative template learning in group-convolutional networks for invariant speech representations - Chiyuan Zhang; Stephen Voinea; Georgios Evangelopoulos; Lorenzo Rosasco; Tomaso A. Poggio (16th Annual Conference of the International Speech Communication Association, INTERSPEECH 2015, Dresden, Germany, September 6-10, 2015, 2015)

Learning with Incremental Iterative Regularization - Lorenzo Rosasco; Silvia Villa (Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada, 2015)

Less is More: Nyström Computational Regularization - Alessandro Rudi; Raffaello Camoriano; Lorenzo Rosasco (Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada, 2015)

On Invariance and Selectivity in Representation Learning - Fabio Anselmi; Lorenzo Rosasco; Tomaso A. Poggio (CoRR, 2015)

Convex Learning of Multiple Tasks and their Structure - Carlo Ciliberto; Youssef Mroueh; Tomaso A. Poggio; Lorenzo Rosasco (CoRR, 2015)

Learning Multiple Visual Tasks while Discovering their Structure - Carlo Ciliberto; Lorenzo Rosasco; Silvia Villa (CoRR, 2015)

Real-world Object Recognition with Off-the-shelf Deep Conv Nets: How Many Objects can iCub Learn? - Giulia Pasquale; Carlo Ciliberto; Francesca Odone; Lorenzo Rosasco; Lorenzo Natale (CoRR, 2015)

Less is More: Nyström Computational Regularization - Alessandro Rudi; Raffaello Camoriano; Lorenzo Rosasco (CoRR, 2015)

Deep Convolutional Networks are Hierarchical Kernel Machines - Fabio Anselmi; Lorenzo Rosasco; Cheston Tan; Tomaso A. Poggio (CoRR, 2015)

Enabling Depth-driven Visual Attention on the iCub Humanoid Robot: Instructions for Use and New Perspectives - Giulia Pasquale; Tanis Mar; Carlo Ciliberto; Lorenzo Rosasco; Lorenzo Natale (CoRR, 2015)

Holographic Embeddings of Knowledge Graphs - Maximilian Nickel; Lorenzo Rosasco; Tomaso A. Poggio (CoRR, 2015)

Mathematical and Computational Foundations of Learning Theory (Dagstuhl Seminar 15361) - Matthias Hein; Gábor Lugosi; Lorenzo Rosasco (Dagstuhl Reports, 2015)

Proximal methods for the latent group lasso penalty - Silvia Villa; Lorenzo Rosasco; Sofia Mosci; Alessandro Verri (Comput. Optim. Appl., 2014)

A deep representation for invariance and music classification - Chiyuan Zhang; Georgios Evangelopoulos; Stephen Voinea; Lorenzo Rosasco; Tomaso A. Poggio (IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014, Florence, Italy, May 4-9, 2014, 2014)

Phone classification by a hierarchy of invariant representation layers - Chiyuan Zhang; Stephen Voinea; Georgios Evangelopoulos; Lorenzo Rosasco; Tomaso A. Poggio (15th Annual Conference of the International Speech Communication Association, INTERSPEECH 2014, Singapore, September 14-18, 2014, 2014)

Word-level invariant representations from acoustic waveforms - Stephen Voinea; Chiyuan Zhang; Georgios Evangelopoulos; Lorenzo Rosasco; Tomaso A. Poggio (15th Annual Conference of the International Speech Communication Association, INTERSPEECH 2014, Singapore, September 14-18, 2014, 2014)

Exploiting global force torque measurements for local compliance estimation in tactile arrays - Carlo Ciliberto; Luca Fiorio; Marco Maggiali; Lorenzo Natale; Lorenzo Rosasco; Giorgio Metta; Giulio Sandini; Francesco Nori (2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014, Chicago, IL, USA, September 14-18, 2014, 2014)

On efficiency and low sample complexity in phase retrieval - Youssef Mroueh; Lorenzo Rosasco (2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29 - July 4, 2014, 2014)

A Deep Representation for Invariance And Music Classification - Chiyuan Zhang; Georgios Evangelopoulos; Stephen Voinea; Lorenzo Rosasco; Tomaso A. Poggio (CoRR, 2014)

Regularization by Early Stopping for Online Learning Algorithms - Lorenzo Rosasco; Andrea Tacchetti; Silvia Villa (CoRR, 2014)

Learning An Invariant Speech Representation - Georgios Evangelopoulos; Stephen Voinea; Chiyuan Zhang; Lorenzo Rosasco; Tomaso A. Poggio (CoRR, 2014)

Nonparametric sparsity and regularization - Lorenzo Rosasco; Silvia Villa; Sofia Mosci; Matteo Santoro; Alessandro Verri (J. Mach. Learn. Res., 2013)

GURLS: a least squares library for supervised learning - Andrea Tacchetti; Pavan Kumar Mallapragada; Matteo Santoro; Lorenzo Rosasco (J. Mach. Learn. Res., 2013)

On Learnability, Complexity and Stability - Silvia Villa; Lorenzo Rosasco; Tomaso A. Poggio (Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013)

iCub World: Friendly Robots Help Building Good Vision Data-Sets - Sean Ryan Fanello; Carlo Ciliberto; Matteo Santoro; Lorenzo Natale; Giorgio Metta; Lorenzo Rosasco; Francesca Odone (IEEE Conference on Computer Vision and Pattern Recognition, CVPR Workshops 2013, Portland, OR, USA, June 23-28, 2013, 2013)

On the impact of learning hierarchical representations for visual recognition in robotics - Carlo Ciliberto; Sean Ryan Fanello; Matteo Santoro; Lorenzo Natale; Giorgio Metta; Lorenzo Rosasco (2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2013, Tokyo, Japan, November 3-7, 2013, 2013)

On the Sample Complexity of Subspace Learning - Alessandro Rudi; Guillermo D. Cañas; Lorenzo Rosasco (Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013, Lake Tahoe, Nevada, United States, 2013)

q-ary Compressive Sensing - Youssef Mroueh; Lorenzo Rosasco (CoRR, 2013)

GURLS: a Least Squares Library for Supervised Learning - Andrea Tacchetti; Pavan Kumar Mallapragada; Matteo Santoro; Lorenzo Rosasco (CoRR, 2013)

On Learnability, Complexity and Stability - Silvia Villa; Lorenzo Rosasco; Tomaso A. Poggio (CoRR, 2013)

iCub World: Friendly Robots Help Building Good Vision Data-Sets - Sean Ryan Fanello; Carlo Ciliberto; Matteo Santoro; Lorenzo Natale; Giorgio Metta; Lorenzo Rosasco; Francesca Odone (CoRR, 2013)

Unsupervised Learning of Invariant Representations in Hierarchical Architectures - Fabio Anselmi; Joel Z. Leibo; Lorenzo Rosasco; Jim Mutch; Andrea Tacchetti; Tomaso A. Poggio (CoRR, 2013)

Quantization and Greed are Good: One bit Phase Retrieval, Robustness and Greedy Refinements - Youssef Mroueh; Lorenzo Rosasco (CoRR, 2013)

Kernels for Vector-Valued Functions: A Review - Mauricio A. Álvarez; Lorenzo Rosasco; Neil D. Lawrence (Found. Trends Mach. Learn., 2012)

Multi-output learning via spectral filtering - Luca Baldassarre; Lorenzo Rosasco; Annalisa Barla; Alessandro Verri (Mach. Learn., 2012)

Learning Manifolds with K-Means and K-Flats - Guillermo D. Cañas; Tomaso A. Poggio; Lorenzo Rosasco (Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012, Lake Tahoe, Nevada, United States, 2012)

Learning Probability Measures with respect to Optimal Transport Metrics - Guillermo D. Cañas; Lorenzo Rosasco (Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012, Lake Tahoe, Nevada, United States, 2012)

Multiclass Learning with Simplex Coding - Youssef Mroueh; Tomaso A. Poggio; Lorenzo Rosasco; Jean-Jacques E. Slotine (Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012, Lake Tahoe, Nevada, United States, 2012)

Nonparametric sparsity and regularization - Lorenzo Rosasco; Silvia Villa; Sofia Mosci; Matteo Santoro; Alessandro Verri (CoRR, 2012)

Proximal methods for the latent group lasso penalty - Silvia Villa; Lorenzo Rosasco; Sofia Mosci; Alessandro Verri (CoRR, 2012)

Learning Probability Measures with respect to Optimal Transport Metrics - Guillermo D. Cañas; Lorenzo Rosasco (CoRR, 2012)

Learning Manifolds with K-Means and K-Flats - Guillermo D. Cañas; Tomaso A. Poggio; Lorenzo Rosasco (CoRR, 2012)

Multiclass Learning with Simplex Coding - Youssef Mroueh; Tomaso A. Poggio; Lorenzo Rosasco; Jean-Jacques E. Slotine (CoRR, 2012)

Online Learning, Stability, and Stochastic Gradient Descent - Tomaso A. Poggio; Stephen Voinea; Lorenzo Rosasco (CoRR, 2011)

Kernels for Vector-Valued Functions: a Review - Mauricio A. Álvarez; Lorenzo Rosasco; Neil D. Lawrence (CoRR, 2011)

Mathematical and Computational Foundations of Learning Theory (Dagstuhl Seminar 11291) - Matthias Hein; Gábor Lugosi; Lorenzo Rosasco; Steve Smale (Dagstuhl Reports, 2011)

Mathematics of the Neural Response - Steve Smale; Lorenzo Rosasco; Jake V. Bouvrie; Andrea Caponnetto; Tomaso A. Poggio (Found. Comput. Math., 2010)

Adaptive Kernel Methods Using the Balancing Principle - Ernesto De Vito; Sergei V. Pereverzyev; Lorenzo Rosasco (Found. Comput. Math., 2010)

On Learning with Integral Operators - Lorenzo Rosasco; Mikhail Belkin; Ernesto De Vito (J. Mach. Learn. Res., 2010)

Spectral Regularization for Support Estimation - Ernesto De Vito; Lorenzo Rosasco; Alessandro Toigo (Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, Vancouver, British Columbia, Canada, 2010)

A Primal-Dual Algorithm for Group Sparse Regularization with Overlapping Groups - Sofia Mosci; Silvia Villa; Alessandro Verri; Lorenzo Rosasco (Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, Vancouver, British Columbia, Canada, 2010)

Vector Field Learning via Spectral Filtering - Luca Baldassarre; Lorenzo Rosasco; Annalisa Barla; Alessandro Verri (Machine Learning and Knowledge Discovery in Databases, European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010, Proceedings, Part I, 2010)

Solving Structured Sparsity Regularization with Proximal Methods - Sofia Mosci; Lorenzo Rosasco; Matteo Santoro; Alessandro Verri; Silvia Villa (Machine Learning and Knowledge Discovery in Databases, European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010, Proceedings, Part II, 2010)

A Regularization Approach to Nonlinear Variable Selection - Lorenzo Rosasco; Matteo Santoro; Sofia Mosci; Alessandro Verri; Silvia Villa (Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2010, Chia Laguna Resort, Sardinia, Italy, May 13-15, 2010, 2010)

Elastic-net regularization in learning theory - Christine De Mol; Ernesto De Vito; Lorenzo Rosasco (J. Complex., 2009)

A Note on Learning with Integral Operators - Lorenzo Rosasco; Mikhail Belkin; Ernesto De Vito (COLT 2009 - The 22nd Conference on Learning Theory, Montreal, Quebec, Canada, June 18-21, 2009, 2009)

Towards a Theoretical Framework for Learning Multi-modal Patterns for Embodied Agents - Nicoletta Noceti; Barbara Caputo; Claudio Castellini; Luca Baldassarre; Annalisa Barla; Lorenzo Rosasco; Francesca Odone; Giulio Sandini (Image Analysis and Processing - ICIAP 2009, 15th International Conference Vietri sul Mare, Italy, September 8-11, 2009, Proceedings, 2009)

On Invariance in Hierarchical Models - Jake V. Bouvrie; Lorenzo Rosasco; Tomaso A. Poggio (Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, Vancouver, British Columbia, Canada, 2009)

Spectral Algorithms for Supervised Learning - L. Lo Gerfo; Lorenzo Rosasco; Francesca Odone; Ernesto De Vito; Alessandro Verri (Neural Comput., 2008)

A method for robust variable selection with significance assessment - Annalisa Barla; Sofia Mosci; Lorenzo Rosasco; Alessandro Verri (16th European Symposium on Artificial Neural Networks, ESANN 2008, Bruges, Belgium, April 23-25, 2008, Proceedings, 2008)

On regularization algorithms in learning theory - Frank Bauer; Sergei V. Pereverzev; Lorenzo Rosasco (J. Complex., 2007)

Dimensionality reduction and generalization - Sofia Mosci; Lorenzo Rosasco; Alessandro Verri (Machine Learning, Proceedings of the Twenty-Fourth International Conference (ICML 2007), Corvallis, Oregon, USA, June 20-24, 2007, 2007)

Regularization approaches in learning theory - Lorenzo Rosasco (University of Genoa, Italy, 2006)

Model Selection for Regularized Least-Squares Algorithm in Learning Theory - Ernesto De Vito; Andrea Caponnetto; Lorenzo Rosasco (Found. Comput. Math., 2005)

Learning from Examples as an Inverse Problem - Ernesto De Vito; Lorenzo Rosasco; Andrea Caponnetto; Umberto De Giovannini; Francesca Odone (J. Mach. Learn. Res., 2005)

Support vector algorithms as regularization networks - Andrea Caponnetto; Lorenzo Rosasco; Francesca Odone; Alessandro Verri (13th European Symposium on Artificial Neural Networks, ESANN 2005, Bruges, Belgium, April 27-29, 2005, Proceedings, 2005)

Some Properties of Regularized Kernel Methods - Ernesto De Vito; Lorenzo Rosasco; Andrea Caponnetto; Michele Piana; Alessandro Verri (J. Mach. Learn. Res., 2004)

Are Loss Functions All the Same? - Lorenzo Rosasco; Ernesto De Vito; Andrea Caponnetto; Michele Piana; Alessandro Verri (Neural Comput., 2004)

Learning, Regularization and Ill-Posed Inverse Problems - Lorenzo Rosasco; Andrea Caponnetto; Ernesto De Vito; Francesca Odone; Umberto De Giovannini (Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, NIPS 2004, December 13-18, 2004, Vancouver, British Columbia, Canada], 2004)