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

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

Towards a learning theory of representation alignment. - Insulla, Francesco; Huang, Shuo; Rosasco, Lorenzo (2025)

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

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

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

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

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

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

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

A structured prediction approach for robot imitation learning. - Duan, Anqing; Batzianoulis, Iason; Camoriano, Raffaello; Rosasco, Lorenzo; Pucci, Daniele; Billard, Aude (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. - Alfano, Paolo Didier; Pastore, Vito Paolo; Rosasco, Lorenzo; Odone, Francesca (Image Vis. Comput., 2024)

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

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

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

Sim2Real Bilevel Adaptation for Object Surface Classification using Vision-Based Tactile Sensors. - Caddeo, Gabriele M.; Maracani, Andrea; Alfano, Paolo Didier; Piga, Nicola A.; Rosasco, Lorenzo; Natale, Lorenzo (2024)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Heteroscedastic Gaussian Processes and Random Features: Scalable Motion Primitives with Guarantees. - Caldarelli, Edoardo; Chatalic, Antoine; Colomé, Adrià; Rosasco, Lorenzo; Torras, Carme (2023)

Regularization Properties of Dual Subgradient Flow. - Apidopoulos, Vassilis; Molinari, Cesare; Rosasco, Lorenzo; Villa, Silvia (2023)

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

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

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

An Optimal Structured Zeroth-order Algorithm for Non-smooth Optimization. - Rando, Marco; Molinari, Cesare; Rosasco, Lorenzo; Villa, Silvia (2023)

The Thirty Sixth Annual Conference on Learning Theory, COLT 2023, 12-15 July 2023, Bangalore, India. (PMLR, 2023)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domains by Adaptive Discretization. - Rando, Marco; Carratino, Luigi; Villa, Silvia; Rosasco, Lorenzo (2022)

Mean Nyström Embeddings for Adaptive Compressive Learning. - Chatalic, Antoine; Carratino, Luigi; Vito, Ernesto De; Rosasco, Lorenzo (2022)

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

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

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

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

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

From Handheld to Unconstrained Object Detection: a Weakly-supervised On-line Learning Approach. - Maiettini, Elisa; Maracani, Andrea; Camoriano, Raffaello; Pasquale, Giulia; Tikhanoff, Vadim; Rosasco, Lorenzo; Natale, Lorenzo (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). - Viceconte, Paolo Maria; Camoriano, Raffaello; Romualdi, Giulio; Ferigo, Diego; Dafarra, Stefano; Traversaro, Silvio; Oriolo, Giuseppe; Rosasco, Lorenzo; Pucci, Daniele (Zenodo, 2022)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Iterative regularization for convex regularizers. - Molinari, Cesare; Massias, Mathurin; Rosasco, Lorenzo; Villa, Silvia (2021)

Asymptotics of Ridge(less) Regression under General Source Condition. - Richards, Dominic; Mourtada, Jaouad; Rosasco, Lorenzo (2021)

Regularized ERM on random subspaces. - Vecchia, Andrea Della; Mourtada, Jaouad; Vito, Ernesto De; Rosasco, Lorenzo (2021)

Fast Object Segmentation Learning with Kernel-based Methods for Robotics. - Ceola, Federico; Maiettini, Elisa; Pasquale, Giulia; Rosasco, Lorenzo; Natale, Lorenzo (2021)

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

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

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

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

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

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

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

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

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

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

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

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

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

Gain with no Pain: Efficiency of Kernel-PCA by Nyström Sampling. - Sterge, Nicholas; Sriperumbudur, Bharath K.; Rosasco, Lorenzo; Rudi, Alessandro (2020)

Near-linear time Gaussian process optimization with adaptive batching and resparsification. - Calandriello, Daniele; Carratino, Luigi; Lazaric, Alessandro; Valko, Michal; Rosasco, Lorenzo (2020)

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

Kernel Methods Through the Roof: Handling Billions of Points Efficiently. - Meanti, Giacomo; Carratino, Luigi; Rosasco, Lorenzo; Rudi, Alessandro (2020)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

A Weakly Supervised Strategy for Learning Object Detection on a Humanoid Robot. - Maiettini, Elisa; Pasquale, Giulia; Tikhanoff, Vadim; Rosasco, Lorenzo; Natale, Lorenzo (2019)

Genuine Personality Recognition from Highly Constrained Face Images. - Anselmi, Fabio; Noceti, Nicoletta; Rosasco, Lorenzo; Ward, Robert (2019)

Learning to Sequence Multiple Tasks with Competing Constraints. - Duan, Anqing; Camoriano, Raffaello; Ferigo, Diego; Huang, Yanlong; Calandriello, Daniele; Rosasco, Lorenzo; Pucci, Daniele (2019)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Solving lp-norm regularization with tensor kernels. - Salzo, Saverio; Rosasco, Lorenzo; Suykens, Johan A. K. (2018)

Iterate Averaging as Regularization for Stochastic Gradient Descent. - Neu, Gergely; Rosasco, Lorenzo (2018)

Sparse Multiple Kernel Learning: Support Identification via Mirror Stratifiability. - Garrigos, Guillaume; Rosasco, Lorenzo; Villa, Silvia (2018)

Constrained DMPs for Feasible Skill Learning on Humanoid Robots. - Duan, Anqing; Camoriano, Raffaello; Ferigo, Diego; Calandriello, Daniele; Rosasco, Lorenzo; Pucci, Daniele (2018)

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

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

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

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

Statistical and Computational Trade-Offs in Kernel K-Means. - Calandriello, Daniele; Rosasco, Lorenzo (2018)

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

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

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

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

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

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

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

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

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

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

Interactive data collection for deep learning object detectors on humanoid robots. - Maiettini, Elisa; Pasquale, Giulia; Rosasco, Lorenzo; Natale, Lorenzo (2017)

Incremental robot learning of new objects with fixed update time. - Camoriano, Raffaello; Pasquale, Giulia; Ciliberto, Carlo; Natale, Lorenzo; Rosasco, Lorenzo; Metta, Giorgio (2017)

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

Generalization Properties of Learning with Random Features. - Rudi, Alessandro; Rosasco, Lorenzo (2017)

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

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

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

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

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

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

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

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

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

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

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

Holographic Embeddings of Knowledge Graphs. - Nickel, Maximilian; Rosasco, Lorenzo; Poggio, Tomaso A. (2016)

NYTRO: When Subsampling Meets Early Stopping. - Camoriano, Raffaello; Angles, Tomás; Rudi, Alessandro; Rosasco, Lorenzo (2016)

Combining sensory modalities and exploratory procedures to improve haptic object recognition in robotics. - Higy, Bertrand; Ciliberto, Carlo; Rosasco, Lorenzo; Natale, Lorenzo (2016)

Active perception: Building objects' models using tactile exploration. - Jamali, Nawid; Ciliberto, Carlo; Rosasco, Lorenzo; Natale, Lorenzo (2016)

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

Incremental semiparametric inverse dynamics learning. - Camoriano, Raffaello; Traversaro, Silvio; Rosasco, Lorenzo; Metta, Giorgio; Nori, Francesco (2016)

Object identification from few examples by improving the invariance of a Deep Convolutional Neural Network. - Pasquale, Giulia; Ciliberto, Carlo; Rosasco, Lorenzo; Natale, Lorenzo (2016)

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

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

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

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

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

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

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

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

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

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

Learning multiple visual tasks while discovering their structure. - Ciliberto, Carlo; Rosasco, Lorenzo; Villa, Silvia (2015)

Teaching iCub to recognize objects using deep Convolutional Neural Networks. - Pasquale, Giulia; Ciliberto, Carlo; Odone, Francesca; Rosasco, Lorenzo; Natale, Lorenzo (2015)

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

Discovering discrete subword units with binarized autoencoders and hidden-Markov-model encoders. - Badino, Leonardo; Mereta, Alessio; Rosasco, Lorenzo (2015)

Discriminative template learning in group-convolutional networks for invariant speech representations. - Zhang, Chiyuan; Voinea, Stephen; Evangelopoulos, Georgios; Rosasco, Lorenzo; Poggio, Tomaso A. (2015)

Learning with Incremental Iterative Regularization. - Rosasco, Lorenzo; Villa, Silvia (2015)

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

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

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

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

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

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

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

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

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

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

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

A deep representation for invariance and music classification. - Zhang, Chiyuan; Evangelopoulos, Georgios; Voinea, Stephen; Rosasco, Lorenzo; Poggio, Tomaso A. (2014)

Phone classification by a hierarchy of invariant representation layers. - Zhang, Chiyuan; Voinea, Stephen; Evangelopoulos, Georgios; Rosasco, Lorenzo; Poggio, Tomaso A. (2014)

Word-level invariant representations from acoustic waveforms. - Voinea, Stephen; Zhang, Chiyuan; Evangelopoulos, Georgios; Rosasco, Lorenzo; Poggio, Tomaso A. (2014)

Exploiting global force torque measurements for local compliance estimation in tactile arrays. - Ciliberto, Carlo; Fiorio, Luca; Maggiali, Marco; Natale, Lorenzo; Rosasco, Lorenzo; Metta, Giorgio; Sandini, Giulio; Nori, Francesco (2014)

On efficiency and low sample complexity in phase retrieval. - Mroueh, Youssef; Rosasco, Lorenzo (2014)

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

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

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

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

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

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

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

On the impact of learning hierarchical representations for visual recognition in robotics. - Ciliberto, Carlo; Fanello, Sean Ryan; Santoro, Matteo; Natale, Lorenzo; Metta, Giorgio; Rosasco, Lorenzo (2013)

On the Sample Complexity of Subspace Learning. - Rudi, Alessandro; Cañas, Guillermo D.; Rosasco, Lorenzo (2013)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Spectral Regularization for Support Estimation. - Vito, Ernesto De; Rosasco, Lorenzo; Toigo, Alessandro (2010)

A Primal-Dual Algorithm for Group Sparse Regularization with Overlapping Groups. - Mosci, Sofia; Villa, Silvia; Verri, Alessandro; Rosasco, Lorenzo (2010)

Vector Field Learning via Spectral Filtering. - Baldassarre, Luca; Rosasco, Lorenzo; Barla, Annalisa; Verri, Alessandro (2010)

Solving Structured Sparsity Regularization with Proximal Methods. - Mosci, Sofia; Rosasco, Lorenzo; Santoro, Matteo; Verri, Alessandro; Villa, Silvia (2010)

A Regularization Approach to Nonlinear Variable Selection. - Rosasco, Lorenzo; Santoro, Matteo; Mosci, Sofia; Verri, Alessandro; Villa, Silvia (2010)

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

A Note on Learning with Integral Operators. - Rosasco, Lorenzo; Belkin, Mikhail; Vito, Ernesto De (2009)

Towards a Theoretical Framework for Learning Multi-modal Patterns for Embodied Agents. - Noceti, Nicoletta; Caputo, Barbara; Castellini, Claudio; Baldassarre, Luca; Barla, Annalisa; Rosasco, Lorenzo; Odone, Francesca; Sandini, Giulio (2009)

On Invariance in Hierarchical Models. - Bouvrie, Jake V.; Rosasco, Lorenzo; Poggio, Tomaso A. (2009)

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

A method for robust variable selection with significance assessment. - Barla, Annalisa; Mosci, Sofia; Rosasco, Lorenzo; Verri, Alessandro (2008)

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

Dimensionality reduction and generalization. - Mosci, Sofia; Rosasco, Lorenzo; Verri, Alessandro (2007)

Regularization approaches in learning theory. - Rosasco, Lorenzo (2006)

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

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

Support vector algorithms as regularization networks. - Caponnetto, Andrea; Rosasco, Lorenzo; Odone, Francesca; Verri, Alessandro (2005)

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

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

Learning, Regularization and Ill-Posed Inverse Problems. - Rosasco, Lorenzo; Caponnetto, Andrea; Vito, Ernesto De; Odone, Francesca; Giovannini, Umberto De (2004)