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ORCIDLorenzo Rosasco
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- affiliation: MIT, Cambridge, MA, USA
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2020 – today
- 2024
[j47]Marco Rando
, Cesare Molinari, Silvia Villa, Lorenzo Rosasco:
Stochastic zeroth order descent with structured directions. Comput. Optim. Appl. 89(3): 691-727 (2024)- [j46]Anqing Duan, Iason Batzianoulis, Raffaello Camoriano, Lorenzo Rosasco, Daniele Pucci, Aude Billard:
A structured prediction approach for robot imitation learning. Int. J. Robotics Res. 43(2): 113-133 (2024) - [j45]Paolo Didier Alfano, Vito Paolo Pastore, Lorenzo Rosasco, Francesca Odone:
Top-tuning: A study on transfer learning for an efficient alternative to fine tuning for image classification with fast kernel methods. Image Vis. Comput. 142: 104894 (2024) - [j44]Cesare Molinari, Mathurin Massias, Lorenzo Rosasco, Silvia Villa:
Iterative regularization for low complexity regularizers. Numerische Mathematik 156(2): 641-689 (2024) - [j43]Federico Ceola, Lorenzo Rosasco, Lorenzo Natale:
RESPRECT: Speeding-up Multi-Fingered Grasping With Residual Reinforcement Learning. IEEE Robotics Autom. Lett. 9(4): 3045-3052 (2024) - [c90]Carlotta Sartore, Marco Rando, Giulio Romualdi, Cesare Molinari, Lorenzo Rosasco, Daniele Pucci:
Automatic Gain Tuning for Humanoid Robots Walking Architectures Using Gradient-Free Optimization Techniques. Humanoids 2024: 996-1003 - [c89]Gabriele M. Caddeo, Andrea Maracani, Paolo Didier Alfano, Nicola A. Piga, Lorenzo Rosasco, Lorenzo Natale:
Sim2Real Bilevel Adaptation for Object Surface Classification using Vision-Based Tactile Sensors. ICRA 2024: 15128-15134 - [i110]Federico Ceola, Lorenzo Rosasco, Lorenzo Natale:
RESPRECT: Speeding-up Multi-fingered Grasping with Residual Reinforcement Learning. CoRR abs/2401.14858 (2024) - [i109]Andrea Maracani, Raffaello Camoriano, Elisa Maiettini, Davide Talon, Lorenzo Rosasco, Lorenzo Natale:
Key Design Choices in Source-Free Unsupervised Domain Adaptation: An In-depth Empirical Analysis. CoRR abs/2402.16090 (2024) - [i108]Edoardo Caldarelli, Antoine Chatalic, Adrià Colomé, Cesare Molinari, Carlos Ocampo-Martinez, Carme Torras, Lorenzo Rosasco:
Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström method. CoRR abs/2403.02811 (2024) - [i107]Francesca Bartolucci, Ernesto De Vito, Lorenzo Rosasco, Stefano Vigogna:
Neural reproducing kernel Banach spaces and representer theorems for deep networks. CoRR abs/2403.08750 (2024) - [i106]Marco Rando, Martin James, Alessandro Verri, Lorenzo Rosasco, Agnese Seminara:
Q-Learning to navigate turbulence without a map. CoRR abs/2404.17495 (2024) - [i105]Marco Rando, Luca Demetrio, Lorenzo Rosasco, Fabio Roli:
A New Formulation for Zeroth-Order Optimization of Adversarial EXEmples in Malware Detection. CoRR abs/2405.14519 (2024) - [i104]Andrea Maracani, Lorenzo Rosasco, Lorenzo Natale:
Trust And Balance: Few Trusted Samples Pseudo-Labeling and Temperature Scaled Loss for Effective Source-Free Unsupervised Domain Adaptation. CoRR abs/2409.00741 (2024) - [i103]Carlotta Sartore, Marco Rando, Giulio Romualdi, Cesare Molinari, Lorenzo Rosasco, Daniele Pucci:
Automatic Gain Tuning for Humanoid Robots Walking Architectures Using Gradient-Free Optimization Techniques. CoRR abs/2409.18649 (2024) - [i102]Hippolyte Labarrière, Cesare Molinari, Lorenzo Rosasco, Silvia Villa, Cristian Vega:
Optimization Insights into Deep Diagonal Linear Networks. CoRR abs/2412.16765 (2024) - 2023
- [j42]Bernhard Stankewitz, Nicole Mücke, Lorenzo Rosasco:
From inexact optimization to learning via gradient concentration. Comput. Optim. Appl. 84(1): 265-294 (2023) - [j41]Gaia Grosso, Nicolò Lai, Marco Letizia, Jacopo Pazzini, Marco Rando, Lorenzo Rosasco, Andrea Wulzer, Marco Zanetti:
Fast kernel methods for data quality monitoring as a goodness-of-fit test. Mach. Learn. Sci. Technol. 4(3): 35029 (2023) - [j40]Guillaume Garrigos, Lorenzo Rosasco, Silvia Villa:
Convergence of the forward-backward algorithm: beyond the worst-case with the help of geometry. Math. Program. 198(1): 937-996 (2023) - [j39]David Kozak, Cesare Molinari, Lorenzo Rosasco, Luis Tenorio, Silvia Villa:
Zeroth-order optimization with orthogonal random directions. Math. Program. 199(1): 1179-1219 (2023) - [c88]Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, Francesco Locatello:
Causal Discovery with Score Matching on Additive Models with Arbitrary Noise. CLeaR 2023: 726-751 - [c87]Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, Francesco Locatello:
Scalable Causal Discovery with Score Matching. CLeaR 2023: 752-771 - [c86]Edoardo Caldarelli, Antoine Chatalic, Adrià Colomé, Lorenzo Rosasco, Carme Torras:
Heteroscedastic Gaussian Processes and Random Features: Scalable Motion Primitives with Guarantees. CoRL 2023: 3010-3029 - [c85]Vassilis Apidopoulos, Cesare Molinari, Lorenzo Rosasco, Silvia Villa:
Regularization Properties of Dual Subgradient Flow. ECC 2023: 1-8 - [c84]Federico Ceola, Elisa Maiettini, Lorenzo Rosasco, Lorenzo Natale:
A Grasp Pose is All You Need: Learning Multi-Fingered Grasping with Deep Reinforcement Learning from Vision and Touch. IROS 2023: 2985-2992 - [c83]Giacomo Meanti, Antoine Chatalic, Vladimir Kostic, Pietro Novelli, Massimiliano Pontil, Lorenzo Rosasco:
Estimating Koopman operators with sketching to provably learn large scale dynamical systems. NeurIPS 2023 - [c82]Francesco Montagna, Atalanti-Anastasia Mastakouri, Elias Eulig, Nicoletta Noceti, Lorenzo Rosasco, Dominik Janzing, Bryon Aragam, Francesco Locatello:
Assumption violations in causal discovery and the robustness of score matching. NeurIPS 2023 - [c81]Marco Rando, Cesare Molinari, Lorenzo Rosasco, Silvia Villa:
An Optimal Structured Zeroth-order Algorithm for Non-smooth Optimization. NeurIPS 2023 - [e1]Gergely Neu, Lorenzo Rosasco:
The Thirty Sixth Annual Conference on Learning Theory, COLT 2023, 12-15 July 2023, Bangalore, India. Proceedings of Machine Learning Research 195, PMLR 2023 [contents] - [i101]Andrea Maracani, Raffaello Camoriano, Elisa Maiettini, Davide Talon, Lorenzo Rosasco, Lorenzo Natale:
Key Design Choices for Double-Transfer in Source-Free Unsupervised Domain Adaptation. CoRR abs/2302.05379 (2023) - [i100]Gaia Grosso, Nicolò Lai, Marco Letizia, Jacopo Pazzini, Marco Rando, Lorenzo Rosasco, Andrea Wulzer, Marco Zanetti:
Fast kernel methods for Data Quality Monitoring as a goodness-of-fit test. CoRR abs/2303.05413 (2023) - [i99]Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, Francesco Locatello:
Causal Discovery with Score Matching on Additive Models with Arbitrary Noise. CoRR abs/2304.03265 (2023) - [i98]Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, Francesco Locatello:
Scalable Causal Discovery with Score Matching. CoRR abs/2304.03382 (2023) - [i97]Federico Ceola, Elisa Maiettini, Lorenzo Rosasco, Lorenzo Natale:
A Grasp Pose is All You Need: Learning Multi-fingered Grasping with Deep Reinforcement Learning from Vision and Touch. CoRR abs/2306.03484 (2023) - [i96]Giacomo Meanti, Antoine Chatalic, Vladimir R. Kostic, Pietro Novelli, Massimiliano Pontil, Lorenzo Rosasco:
Estimating Koopman operators with sketching to provably learn large scale dynamical systems. CoRR abs/2306.04520 (2023) - [i95]Anqing Duan, Iason Batzianoulis, Raffaello Camoriano, Lorenzo Rosasco, Daniele Pucci, Aude Billard:
A Structured Prediction Approach for Robot Imitation Learning. CoRR abs/2309.14829 (2023) - [i94]Francesco Montagna, Atalanti-Anastasia Mastakouri, Elias Eulig, Nicoletta Noceti, Lorenzo Rosasco, Dominik Janzing, Bryon Aragam, Francesco Locatello:
Assumption violations in causal discovery and the robustness of score matching. CoRR abs/2310.13387 (2023) - [i93]Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Francesco Locatello:
Shortcuts for causal discovery of nonlinear models by score matching. CoRR abs/2310.14246 (2023) - [i92]Gabriele M. Caddeo, Andrea Maracani, Paolo Didier Alfano, Nicola A. Piga, Lorenzo Rosasco, Lorenzo Natale:
Sim2Real Bilevel Adaptation for Object Surface Classification using Vision-Based Tactile Sensors. CoRR abs/2311.01380 (2023) - [i91]Antoine Chatalic, Nicolas Schreuder, Ernesto De Vito, Lorenzo Rosasco:
Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling. CoRR abs/2311.13548 (2023) - [i90]Anqing Duan, Wanli Liuchen, Jinsong Wu, Raffaello Camoriano, Lorenzo Rosasco, David Navarro-Alarcon:
Learning Rhythmic Trajectories with Geometric Constraints for Laser-Based Skincare Procedures. CoRR abs/2312.13623 (2023) - 2022
- [j38]Paolo Maria Viceconte, Raffaello Camoriano, Giulio Romualdi, Diego Ferigo, Stefano Dafarra, Silvio Traversaro, Giuseppe Oriolo, Lorenzo Rosasco, Daniele Pucci:
ADHERENT: Learning Human-like Trajectory Generators for Whole-body Control of Humanoid Robots. IEEE Robotics Autom. Lett. 7(2): 2779-2786 (2022) - [j37]Cristian Rusu, Lorenzo Rosasco:
Fast approximation of orthogonal matrices and application to PCA. Signal Process. 194: 108451 (2022) - [j36]Federico Ceola, Elisa Maiettini, Giulia Pasquale, Giacomo Meanti, Lorenzo Rosasco, Lorenzo Natale:
Learn Fast, Segment Well: Fast Object Segmentation Learning on the iCub Robot. IEEE Trans. Robotics 38(5): 3154-3172 (2022) - [c80]Giacomo Meanti, Luigi Carratino, Ernesto De Vito, Lorenzo Rosasco:
Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression. AISTATS 2022: 6554-6572 - [c79]Marco Rando, Luigi Carratino, Silvia Villa, Lorenzo Rosasco:
Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domains by Adaptive Discretization. AISTATS 2022: 7320-7348 - [c78]Antoine Chatalic, Luigi Carratino, Ernesto De Vito, Lorenzo Rosasco:
Mean Nyström Embeddings for Adaptive Compressive Learning. AISTATS 2022: 9869-9889 - [c77]Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco:
Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times. ICML 2022: 2523-2541 - [c76]Antoine Chatalic, Nicolas Schreuder, Lorenzo Rosasco, Alessandro Rudi:
Nyström Kernel Mean Embeddings. ICML 2022: 3006-3024 - [c75]Stefano Vigogna, Giacomo Meanti, Ernesto De Vito, Lorenzo Rosasco:
Multiclass learning with margin: exponential rates with no bias-variance trade-off. ICML 2022: 22260-22269 - [c74]Paolo Didier Alfano, Marco Rando, Marco Letizia, Francesca Odone, Lorenzo Rosasco, Vito Paolo Pastore:
Efficient Unsupervised Learning for Plankton Images. ICPR 2022: 1314-1321 - [c73]Vladimir Kostic, Pietro Novelli, Andreas Maurer, Carlo Ciliberto, Lorenzo Rosasco, Massimiliano Pontil:
Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces. NeurIPS 2022 - [c72]Elisa Maiettini, Andrea Maracani, Raffaello Camoriano, Giulia Pasquale, Vadim Tikhanoff, Lorenzo Rosasco, Lorenzo Natale:
From Handheld to Unconstrained Object Detection: a Weakly-supervised On-line Learning Approach. RO-MAN 2022: 942-949 - [i89]Giacomo Meanti, Luigi Carratino, Ernesto De Vito, Lorenzo Rosasco:
Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression. CoRR abs/2201.06314 (2022) - [i88]Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco:
Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times. CoRR abs/2201.12909 (2022) - [i87]Antoine Chatalic, Nicolas Schreuder, Alessandro Rudi, Lorenzo Rosasco:
Nyström Kernel Mean Embeddings. CoRR abs/2201.13055 (2022) - [i86]Stefano Vigogna, Giacomo Meanti, Ernesto De Vito, Lorenzo Rosasco:
Multiclass learning with margin: exponential rates with no bias-variance trade-off. CoRR abs/2202.01773 (2022) - [i85]Jaouad Mourtada, Lorenzo Rosasco:
An elementary analysis of ridge regression with random design. CoRR abs/2203.08564 (2022) - [i84]Daniele Lagomarsino-Oneto, Giacomo Meanti, Nicolò Pagliana, Alessandro Verri, Andrea Mazzino, Lorenzo Rosasco, Agnese Seminara:
Physics Informed Shallow Machine Learning for Wind Speed Prediction. CoRR abs/2204.00495 (2022) - [i83]Marco Letizia, Gianvito Losapio, Marco Rando, Gaia Grosso, Andrea Wulzer, Maurizio Pierini, Marco Zanetti, Lorenzo Rosasco:
Learning new physics efficiently with nonparametric methods. CoRR abs/2204.02317 (2022) - [i82]Vladimir Kostic, Pietro Novelli, Andreas Maurer, Carlo Ciliberto, Lorenzo Rosasco, Massimiliano Pontil:
Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces. CoRR abs/2205.14027 (2022) - [i81]Marco Rando, Cesare Molinari, Silvia Villa, Lorenzo Rosasco:
Stochastic Zeroth order Descent with Structured Directions. CoRR abs/2206.05124 (2022) - [i80]Federico Ceola, Elisa Maiettini, Giulia Pasquale, Giacomo Meanti, Lorenzo Rosasco, Lorenzo Natale:
Learn Fast, Segment Well: Fast Object Segmentation Learning on the iCub Robot. CoRR abs/2206.13462 (2022) - [i79]Emilia Magnani, Nicholas Krämer, Runa Eschenhagen, Lorenzo Rosasco, Philipp Hennig:
Approximate Bayesian Neural Operators: Uncertainty Quantification for Parametric PDEs. CoRR abs/2208.01565 (2022) - [i78]Paolo Didier Alfano, Marco Rando, Marco Letizia, Francesca Odone, Lorenzo Rosasco, Vito Paolo Pastore:
Efficient Unsupervised Learning for Plankton Images. CoRR abs/2209.06726 (2022) - [i77]Paolo Didier Alfano, Vito Paolo Pastore, Lorenzo Rosasco, Francesca Odone:
Fine-tuning or top-tuning? Transfer learning with pretrained features and fast kernel methods. CoRR abs/2209.07932 (2022) - [i76]Vassilis Apidopoulos, Tomaso A. Poggio, Lorenzo Rosasco, Silvia Villa:
Iterative regularization in classification via hinge loss diagonal descent. CoRR abs/2212.12675 (2022) - 2021
- [j35]Gian Maria Marconi, Raffaello Camoriano, Lorenzo Rosasco, Carlo Ciliberto:
Structured Prediction for CRiSP Inverse Kinematics Learning With Misspecified Robot Models. IEEE Robotics Autom. Lett. 6(3): 5650-5657 (2021) - [j34]Diego Ferigo, Raffaello Camoriano, Paolo Maria Viceconte, Daniele Calandriello, Silvio Traversaro, Lorenzo Rosasco, Daniele Pucci:
On the Emergence of Whole-Body Strategies From Humanoid Robot Push-Recovery Learning. IEEE Robotics Autom. Lett. 6(4): 8561-8568 (2021) - [j33]Luca Calatroni, Guillaume Garrigos, Lorenzo Rosasco, Silvia Villa:
Accelerated Iterative Regularization via Dual Diagonal Descent. SIAM J. Optim. 31(1): 754-784 (2021) - [j32]Cristian Rusu, Lorenzo Rosasco:
Constructing Fast Approximate Eigenspaces With Application to the Fast Graph Fourier Transforms. IEEE Trans. Signal Process. 69: 5037-5050 (2021) - [c71]Cesare Molinari, Mathurin Massias, Lorenzo Rosasco, Silvia Villa:
Iterative regularization for convex regularizers. AISTATS 2021: 1684-1692 - [c70]Dominic Richards, Jaouad Mourtada, Lorenzo Rosasco:
Asymptotics of Ridge(less) Regression under General Source Condition. AISTATS 2021: 3889-3897 - [c69]Andrea Della Vecchia, Jaouad Mourtada, Ernesto De Vito, Lorenzo Rosasco:
Regularized ERM on random subspaces. AISTATS 2021: 4006-4014 - [c68]Federico Ceola, Elisa Maiettini, Giulia Pasquale, Lorenzo Rosasco, Lorenzo Natale:
Fast Object Segmentation Learning with Kernel-based Methods for Robotics. ICRA 2021: 13581-13588 - [c67]Luigi Carratino, Stefano Vigogna, Daniele Calandriello, Lorenzo Rosasco:
ParK: Sound and Efficient Kernel Ridge Regression by Feature Space Partitions. NeurIPS 2021: 6430-6441 - [i75]Gian Maria Marconi, Raffaello Camoriano, Lorenzo Rosasco, Carlo Ciliberto:
Structured Prediction for CRiSP Inverse Kinematics Learning with Misspecified Robot Models. CoRR abs/2102.12942 (2021) - [i74]Diego Ferigo, Raffaello Camoriano, Paolo Maria Viceconte, Daniele Calandriello, Silvio Traversaro, Lorenzo Rosasco, Daniele Pucci:
On the Emergence of Whole-body Strategies from Humanoid Robot Push-recovery Learning. CoRR abs/2104.14534 (2021) - [i73]Bernhard Stankewitz, Nicole Mücke, Lorenzo Rosasco:
From inexact optimization to learning via gradient concentration. CoRR abs/2106.05397 (2021) - [i72]Marco Rando, Luigi Carratino, Silvia Villa, Lorenzo Rosasco:
Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domain by Adaptive Discretization. CoRR abs/2106.08598 (2021) - [i71]Luigi Carratino, Stefano Vigogna, Daniele Calandriello, Lorenzo Rosasco:
ParK: Sound and Efficient Kernel Ridge Regression by Feature Space Partitions. CoRR abs/2106.12231 (2021) - [i70]Francesca Bartolucci, Ernesto De Vito, Lorenzo Rosasco, Stefano Vigogna:
Understanding neural networks with reproducing kernel Banach spaces. CoRR abs/2109.09710 (2021) - [i69]Antoine Chatalic, Luigi Carratino, Ernesto De Vito, Lorenzo Rosasco:
Mean Nyström Embeddings for Adaptive Compressive Learning. CoRR abs/2110.10996 (2021) - 2020
- [j31]Elisa Maiettini, Giulia Pasquale, Lorenzo Rosasco, Lorenzo Natale:
On-line object detection: a robotics challenge. Auton. Robots 44(5): 739-757 (2020) - [j30]Anqing Duan, Raffaello Camoriano, Diego Ferigo, Yanlong Huang, Daniele Calandriello, Lorenzo Rosasco, Daniele Pucci:
Learning to Avoid Obstacles With Minimal Intervention Control. Frontiers Robotics AI 7: 60 (2020) - [j29]Xuefei Lu, Alessandro Rudi, Emanuele Borgonovo, Lorenzo Rosasco:
Faster Kriging: Facing High-Dimensional Simulators. Oper. Res. 68(1): 233-249 (2020) - [j28]Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi:
A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings. J. Mach. Learn. Res. 21: 98:1-98:67 (2020) - [c66]Gian Maria Marconi, Carlo Ciliberto, Lorenzo Rosasco:
Hyperbolic Manifold Regression. AISTATS 2020: 2570-2580 - [c65]Nicholas Sterge, Bharath K. Sriperumbudur, Lorenzo Rosasco, Alessandro Rudi:
Gain with no Pain: Efficiency of Kernel-PCA by Nyström Sampling. AISTATS 2020: 3642-3652 - [c64]Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco:
Near-linear time Gaussian process optimization with adaptive batching and resparsification. ICML 2020: 1295-1305 - [c63]Dominic Richards, Patrick Rebeschini, Lorenzo Rosasco:
Decentralised Learning with Random Features and Distributed Gradient Descent. ICML 2020: 8105-8115 - [c62]Giacomo Meanti, Luigi Carratino, Lorenzo Rosasco, Alessandro Rudi:
Kernel Methods Through the Roof: Handling Billions of Points Efficiently. NeurIPS 2020 - [i68]Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi:
A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings. CoRR abs/2002.05424 (2020) - [i67]Cristian Rusu, Lorenzo Rosasco:
Constructing fast approximate eigenspaces with application to the fast graph Fourier transforms. CoRR abs/2002.09723 (2020) - [i66]Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco:
Near-linear Time Gaussian Process Optimization with Adaptive Batching and Resparsification. CoRR abs/2002.09954 (2020) - [i65]Gian Maria Marconi, Lorenzo Rosasco, Carlo Ciliberto:
Hyperbolic Manifold Regression. CoRR abs/2005.13885 (2020) - [i64]Cesare Molinari, Mathurin Massias, Lorenzo Rosasco, Silvia Villa:
Implicit regularization for convex regularizers. CoRR abs/2006.09859 (2020) - [i63]Andrea Della Vecchia, Jaouad Mourtada, Ernesto De Vito, Lorenzo Rosasco:
Regularized ERM on random subspaces. CoRR abs/2006.10016 (2020) - [i62]Giacomo Meanti, Luigi Carratino, Lorenzo Rosasco, Alessandro Rudi:
Kernel methods through the roof: handling billions of points efficiently. CoRR abs/2006.10350 (2020) - [i61]Akshay Rangamani, Lorenzo Rosasco, Tomaso A. Poggio:
For interpolating kernel machines, the minimum norm ERM solution is the most stable. CoRR abs/2006.15522 (2020) - [i60]Dominic Richards, Patrick Rebeschini, Lorenzo Rosasco:
Decentralised Learning with Random Features and Distributed Gradient Descent. CoRR abs/2007.00360 (2020) - [i59]Federico Ceola, Elisa Maiettini, Giulia Pasquale, Lorenzo Rosasco, Lorenzo Natale:
Fast Region Proposal Learning for Object Detection for Robotics. CoRR abs/2011.12790 (2020) - [i58]Federico Ceola, Elisa Maiettini, Giulia Pasquale, Lorenzo Rosasco, Lorenzo Natale:
Fast Object Segmentation Learning with Kernel-based Methods for Robotics. CoRR abs/2011.12805 (2020) - [i57]Elisa Maiettini, Raffaello Camoriano, Giulia Pasquale, Vadim Tikhanoff, Lorenzo Rosasco, Lorenzo Natale:
Data-efficient Weakly-supervised Learning for On-line Object Detection under Domain Shift in Robotics. CoRR abs/2012.14345 (2020)
2010 – 2019
- 2019
- [j27]Fabio Anselmi, Georgios Evangelopoulos, Lorenzo Rosasco, Tomaso A. Poggio:
Symmetry-adapted representation learning. Pattern Recognit. 86: 201-208 (2019) - [j26]Giulia Pasquale, Carlo Ciliberto, Francesca Odone, Lorenzo Rosasco, Lorenzo Natale:
Are we done with object recognition? The iCub robot's perspective. Robotics Auton. Syst. 112: 260-281 (2019) - [c61]Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco:
Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret. COLT 2019: 533-557 - [c60]Elisa Maiettini, Giulia Pasquale, Vadim Tikhanoff, Lorenzo Rosasco, Lorenzo Natale:
A Weakly Supervised Strategy for Learning Object Detection on a Humanoid Robot. Humanoids 2019: 194-201 - [c59]Fabio Anselmi, Nicoletta Noceti, Lorenzo Rosasco, Robert Ward:
Genuine Personality Recognition from Highly Constrained Face Images. ICIAP (1) 2019: 421-431 - [c58]Anqing Duan, Raffaello Camoriano, Diego Ferigo, Yanlong Huang, Daniele Calandriello, Lorenzo Rosasco, Daniele Pucci:
Learning to Sequence Multiple Tasks with Competing Constraints. IROS 2019: 2672-2678 - [c57]Nicole Mücke, Gergely Neu, Lorenzo Rosasco:
Beating SGD Saturation with Tail-Averaging and Minibatching. NeurIPS 2019: 12568-12577 - [c56]Nicolò Pagliana, Lorenzo Rosasco:
Implicit Regularization of Accelerated Methods in Hilbert Spaces. NeurIPS 2019: 14454-14464 - [i56]Fabio Anselmi, Benedetta Franceschiello, Micah M. Murray, Lorenzo Rosasco:
A computational model for grid maps in neural populations. CoRR abs/1902.06553 (2019) - [i55]Nicole Mücke, Gergely Neu, Lorenzo Rosasco:
Beating SGD Saturation with Tail-Averaging and Minibatching. CoRR abs/1902.08668 (2019) - [i54]Andrzej Banburski, Qianli Liao, Brando Miranda, Lorenzo Rosasco, Bob Liang, Jack Hidary, Tomaso A. Poggio:
Theory III: Dynamics and Generalization in Deep Networks. CoRR abs/1903.04991 (2019) - [i53]Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco:
Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret. CoRR abs/1903.05594 (2019) - [i52]Ernesto De Vito, Nicole Mücke, Lorenzo Rosasco:
Reproducing kernel Hilbert spaces on manifolds: Sobolev and Diffusion spaces. CoRR abs/1905.10913 (2019) - [i51]Nicolò Pagliana, Lorenzo Rosasco:
Implicit Regularization of Accelerated Methods in Hilbert Spaces. CoRR abs/1905.13000 (2019) - [i50]Enrico Cecini, Ernesto De Vito, Lorenzo Rosasco:
Multi-Scale Vector Quantization with Reconstruction Trees. CoRR abs/1907.03875 (2019) - [i49]Nicholas Sterge, Bharath K. Sriperumbudur, Lorenzo Rosasco, Alessandro Rudi:
Gain with no Pain: Efficient Kernel-PCA by Nyström Sampling. CoRR abs/1907.05226 (2019) - [i48]Cristian Rusu, Lorenzo Rosasco:
Fast approximation of orthogonal matrices and application to PCA. CoRR abs/1907.08697 (2019) - [i47]Daniele Calandriello, Lorenzo Rosasco:
Statistical and Computational Trade-Offs in Kernel K-Means. CoRR abs/1908.10284 (2019) - 2018
- [j25]Junhong Lin, Lorenzo Rosasco, Silvia Villa, Ding-Xuan Zhou:
Modified Fejér sequences and applications. Comput. Optim. Appl. 71(1): 95-113 (2018) - [j24]Junhong Lin, Lorenzo Rosasco:
Generalization properties of doubly stochastic learning algorithms. J. Complex. 47: 42-61 (2018) - [j23]Guillaume Garrigos, Lorenzo Rosasco, Silvia Villa:
Iterative Regularization via Dual Diagonal Descent. J. Math. Imaging Vis. 60(2): 189-215 (2018) - [c55]Saverio Salzo, Lorenzo Rosasco, Johan A. K. Suykens:
Solving lp-norm regularization with tensor kernels. AISTATS 2018: 1655-1663 - [c54]Gergely Neu, Lorenzo Rosasco:
Iterate Averaging as Regularization for Stochastic Gradient Descent. COLT 2018: 3222-3242 - [c53]Guillaume Garrigos, Lorenzo Rosasco, Silvia Villa:
Sparse Multiple Kernel Learning: Support Identification via Mirror Stratifiability. EUSIPCO 2018: 1077-1081 - [c52]Anqing Duan, Raffaello Camoriano, Diego Ferigo, Daniele Calandriello, Lorenzo Rosasco, Daniele Pucci:
Constrained DMPs for Feasible Skill Learning on Humanoid Robots. Humanoids 2018: 1-6 - [c51]Elisa Maiettini, Giulia Pasquale, Lorenzo Rosasco, Lorenzo Natale:
Speeding-Up Object Detection Training for Robotics with FALKON. IROS 2018: 5770-5776 - [c50]Alessandro Rudi, Carlo Ciliberto, Gian Maria Marconi, Lorenzo Rosasco:
Manifold Structured Prediction. NeurIPS 2018: 5615-5626 - [c49]Alessandro Rudi, Daniele Calandriello, Luigi Carratino, Lorenzo Rosasco:
On Fast Leverage Score Sampling and Optimal Learning. NeurIPS 2018: 5677-5687 - [c48]Dimitrios Milios, Raffaello Camoriano, Pietro Michiardi, Lorenzo Rosasco, Maurizio Filippone:
Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification. NeurIPS 2018: 6008-6018 - [c47]Daniele Calandriello, Lorenzo Rosasco:
Statistical and Computational Trade-Offs in Kernel K-Means. NeurIPS 2018: 9379-9389 - [c46]Luigi Carratino, Alessandro Rudi, Lorenzo Rosasco:
Learning with SGD and Random Features. NeurIPS 2018: 10213-10224 - [i46]Tomaso A. Poggio, Kenji Kawaguchi, Qianli Liao, Brando Miranda, Lorenzo Rosasco, Xavier Boix, Jack Hidary, Hrushikesh N. Mhaskar:
Theory of Deep Learning III: explaining the non-overfitting puzzle. CoRR abs/1801.00173 (2018) - [i45]Gergely Neu, Lorenzo Rosasco:
Iterate averaging as regularization for stochastic gradient descent. CoRR abs/1802.08009 (2018) - [i44]Elisa Maiettini, Giulia Pasquale, Lorenzo Rosasco, Lorenzo Natale:
Speeding-up Object Detection Training for Robotics with FALKON. CoRR abs/1803.08740 (2018) - [i43]Dimitrios Milios, Raffaello Camoriano, Pietro Michiardi, Lorenzo Rosasco, Maurizio Filippone:
Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification. CoRR abs/1805.10915 (2018) - [i42]Alessandro Rudi, Carlo Ciliberto, Gian Maria Marconi, Lorenzo Rosasco:
Manifold Structured Prediction. CoRR abs/1806.09908 (2018) - [i41]Luigi Carratino, Alessandro Rudi, Lorenzo Rosasco:
Learning with SGD and Random Features. CoRR abs/1807.06343 (2018) - [i40]Alessandro Rudi, Daniele Calandriello, Luigi Carratino, Lorenzo Rosasco:
On Fast Leverage Score Sampling and Optimal Learning. CoRR abs/1810.13258 (2018) - 2017
- [j22]Tomaso A. Poggio, Hrushikesh N. Mhaskar, Lorenzo Rosasco, Brando Miranda, Qianli Liao:
Why and when can deep-but not shallow-networks avoid the curse of dimensionality: A review. Int. J. Autom. Comput. 14(5): 503-519 (2017) - [j21]Junhong Lin, Lorenzo Rosasco:
Optimal Rates for Multi-pass Stochastic Gradient Methods. J. Mach. Learn. Res. 18: 97:1-97:47 (2017) - [c45]Elisa Maiettini, Giulia Pasquale, Lorenzo Rosasco, Lorenzo Natale:
Interactive data collection for deep learning object detectors on humanoid robots. Humanoids 2017: 862-868 - [c44]Raffaello Camoriano, Giulia Pasquale, Carlo Ciliberto, Lorenzo Natale, Lorenzo Rosasco, Giorgio Metta:
Incremental robot learning of new objects with fixed update time. ICRA 2017: 3207-3214 - [c43]Carlo Ciliberto, Alessandro Rudi, Lorenzo Rosasco, Massimiliano Pontil:
Consistent Multitask Learning with Nonlinear Output Relations. NIPS 2017: 1986-1996 - [c42]Alessandro Rudi, Lorenzo Rosasco:
Generalization Properties of Learning with Random Features. NIPS 2017: 3215-3225 - [c41]Alessandro Rudi, Luigi Carratino, Lorenzo Rosasco:
FALKON: An Optimal Large Scale Kernel Method. NIPS 2017: 3888-3898 - [i39]Carlo Ciliberto, Alessandro Rudi, Lorenzo Rosasco, Massimiliano Pontil:
Consistent Multitask Learning with Nonlinear Output Relations. CoRR abs/1705.08118 (2017) - [i38]Alessandro Rudi, Luigi Carratino, Lorenzo Rosasco:
FALKON: An Optimal Large Scale Kernel Method. CoRR abs/1705.10958 (2017) - [i37]Junhong Lin, Lorenzo Rosasco:
Generalization Properties of Doubly Online Learning Algorithms. CoRR abs/1707.00577 (2017) - [i36]Simon Matet, Lorenzo Rosasco, Silvia Villa, Bang Long Vu:
Don't relax: early stopping for convex regularization. CoRR abs/1707.05422 (2017) - [i35]Giulia Pasquale, Carlo Ciliberto, Francesca Odone, Lorenzo Rosasco, Lorenzo Natale:
Are we Done with Object Recognition? The iCub robot's Perspective. CoRR abs/1709.09882 (2017) - [i34]Junhong Lin, Lorenzo Rosasco:
Optimal Rates for Learning with Nyström Stochastic Gradient Methods. CoRR abs/1710.07797 (2017) - 2016
- [j20]Giulia Pasquale, Tanis Mar, Carlo Ciliberto, Lorenzo Rosasco, Lorenzo Natale:
Enabling Depth-Driven Visual Attention on the iCub Humanoid Robot: Instructions for Use and New Perspectives. Frontiers Robotics AI 3: 35 (2016) - [j19]Junhong Lin, Lorenzo Rosasco, Ding-Xuan Zhou:
Iterative Regularization for Learning with Convex Loss Functions. J. Mach. Learn. Res. 17: 77:1-77:38 (2016) - [j18]Lorenzo Rosasco, Silvia Villa, Bang Công Vu:
Stochastic Forward-Backward Splitting for Monotone Inclusions. J. Optim. Theory Appl. 169(2): 388-406 (2016) - [j17]Fabio Anselmi, Joel Z. Leibo, Lorenzo Rosasco, Jim Mutch, Andrea Tacchetti, Tomaso A. Poggio:
Unsupervised learning of invariant representations. Theor. Comput. Sci. 633: 112-121 (2016) - [c40]Maximilian Nickel, Lorenzo Rosasco, Tomaso A. Poggio:
Holographic Embeddings of Knowledge Graphs. AAAI 2016: 1955-1961 - [c39]Raffaello Camoriano, Tomás Angles, Alessandro Rudi, Lorenzo Rosasco:
NYTRO: When Subsampling Meets Early Stopping. AISTATS 2016: 1403-1411 - [c38]Bertrand Higy, Carlo Ciliberto, Lorenzo Rosasco, Lorenzo Natale:
Combining sensory modalities and exploratory procedures to improve haptic object recognition in robotics. Humanoids 2016: 117-124 - [c37]Nawid Jamali, Carlo Ciliberto, Lorenzo Rosasco, Lorenzo Natale:
Active perception: Building objects' models using tactile exploration. Humanoids 2016: 179-185 - [c36]Junhong Lin, Raffaello Camoriano, Lorenzo Rosasco:
Generalization Properties and Implicit Regularization for Multiple Passes SGM. ICML 2016: 2340-2348 - [c35]Raffaello Camoriano, Silvio Traversaro, Lorenzo Rosasco, Giorgio Metta, Francesco Nori:
Incremental semiparametric inverse dynamics learning. ICRA 2016: 544-550 - [c34]Giulia Pasquale, Carlo Ciliberto, Lorenzo Rosasco, Lorenzo Natale:
Object identification from few examples by improving the invariance of a Deep Convolutional Neural Network. IROS 2016: 4904-4911 - [c33]Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi:
A Consistent Regularization Approach for Structured Prediction. NIPS 2016: 4412-4420 - [c32]Junhong Lin, Lorenzo Rosasco:
Optimal Learning for Multi-pass Stochastic Gradient Methods. NIPS 2016: 4556-4564 - [i33]Raffaello Camoriano, Silvio Traversaro, Lorenzo Rosasco, Giorgio Metta, Francesco Nori:
Incremental Semiparametric Inverse Dynamics Learning. CoRR abs/1601.04549 (2016) - [i32]Alessandro Rudi, Raffaello Camoriano, Lorenzo Rosasco:
Generalization Properties of Learning with Random Features. CoRR abs/1602.04474 (2016) - [i31]Raffaello Camoriano, Giulia Pasquale, Carlo Ciliberto, Lorenzo Natale, Lorenzo Rosasco, Giorgio Metta:
Incremental Object Recognition in Robotics with Extension to New Classes in Constant Time. CoRR abs/1605.05045 (2016) - [i30]Carlo Ciliberto, Alessandro Rudi, Lorenzo Rosasco:
A Consistent Regularization Approach for Structured Prediction. CoRR abs/1605.07588 (2016) - [i29]Junhong Lin, Raffaello Camoriano, Lorenzo Rosasco:
Generalization Properties and Implicit Regularization for Multiple Passes SGM. CoRR abs/1605.08375 (2016) - [i28]Junhong Lin, Lorenzo Rosasco:
Optimal Learning for Multi-pass Stochastic Gradient Methods. CoRR abs/1605.08882 (2016) - [i27]Tomaso A. Poggio, Hrushikesh N. Mhaskar, Lorenzo Rosasco, Brando Miranda, Qianli Liao:
Why and When Can Deep - but Not Shallow - Networks Avoid the Curse of Dimensionality: a Review. CoRR abs/1611.00740 (2016) - 2015
- [j16]Gian Luca Breschi, Carlo Ciliberto, Thierry Nieus, Lorenzo Rosasco, Stefano Taverna, Michela Chiappalone, Valentina Pasquale:
Characterizing the Input-Output Function of the Olfactory-Limbic Pathway in the Guinea Pig. Comput. Intell. Neurosci. 2015: 359590:1-359590:11 (2015) - [c31]Carlo Ciliberto, Lorenzo Rosasco, Silvia Villa:
Learning multiple visual tasks while discovering their structure. CVPR 2015: 131-139 - [c30]Giulia Pasquale, Carlo Ciliberto, Francesca Odone, Lorenzo Rosasco, Lorenzo Natale:
Teaching iCub to recognize objects using deep Convolutional Neural Networks. MLIS@ICML 2015: 21-25 - [c29]Carlo Ciliberto, Youssef Mroueh, Tomaso A. Poggio, Lorenzo Rosasco:
Convex Learning of Multiple Tasks and their Structure. ICML 2015: 1548-1557 - [c28]Leonardo Badino, Alessio Mereta, Lorenzo Rosasco:
Discovering discrete subword units with binarized autoencoders and hidden-Markov-model encoders. INTERSPEECH 2015: 3174-3178 - [c27]Chiyuan Zhang, Stephen Voinea, Georgios Evangelopoulos, Lorenzo Rosasco, Tomaso A. Poggio:
Discriminative template learning in group-convolutional networks for invariant speech representations. INTERSPEECH 2015: 3229-3233 - [c26]Lorenzo Rosasco, Silvia Villa:
Learning with Incremental Iterative Regularization. NIPS 2015: 1630-1638 - [c25]Alessandro Rudi, Raffaello Camoriano, Lorenzo Rosasco:
Less is More: Nyström Computational Regularization. NIPS 2015: 1657-1665 - [i26]Fabio Anselmi, Lorenzo Rosasco, Tomaso A. Poggio:
On Invariance and Selectivity in Representation Learning. CoRR abs/1503.05938 (2015) - [i25]Carlo Ciliberto, Youssef Mroueh, Tomaso A. Poggio, Lorenzo Rosasco:
Convex Learning of Multiple Tasks and their Structure. CoRR abs/1504.03101 (2015) - [i24]Carlo Ciliberto, Lorenzo Rosasco, Silvia Villa:
Learning Multiple Visual Tasks while Discovering their Structure. CoRR abs/1504.03106 (2015) - [i23]Giulia Pasquale, Carlo Ciliberto, Francesca Odone, Lorenzo Rosasco, Lorenzo Natale:
Real-world Object Recognition with Off-the-shelf Deep Conv Nets: How Many Objects can iCub Learn? CoRR abs/1504.03154 (2015) - [i22]Alessandro Rudi, Raffaello Camoriano, Lorenzo Rosasco:
Less is More: Nyström Computational Regularization. CoRR abs/1507.04717 (2015) - [i21]Fabio Anselmi, Lorenzo Rosasco, Cheston Tan, Tomaso A. Poggio:
Deep Convolutional Networks are Hierarchical Kernel Machines. CoRR abs/1508.01084 (2015) - [i20]Giulia Pasquale, Tanis Mar, Carlo Ciliberto, Lorenzo Rosasco, Lorenzo Natale:
Enabling Depth-driven Visual Attention on the iCub Humanoid Robot: Instructions for Use and New Perspectives. CoRR abs/1509.06939 (2015) - [i19]Maximilian Nickel, Lorenzo Rosasco, Tomaso A. Poggio:
Holographic Embeddings of Knowledge Graphs. CoRR abs/1510.04935 (2015) - [i18]Matthias Hein, Gábor Lugosi, Lorenzo Rosasco:
Mathematical and Computational Foundations of Learning Theory (Dagstuhl Seminar 15361). Dagstuhl Reports 5(8): 54-0 (2015) - 2014
- [j15]Silvia Villa, Lorenzo Rosasco, Sofia Mosci, Alessandro Verri:
Proximal methods for the latent group lasso penalty. Comput. Optim. Appl. 58(2): 381-407 (2014) - [c24]Chiyuan Zhang, Georgios Evangelopoulos, Stephen Voinea, Lorenzo Rosasco, Tomaso A. Poggio:
A deep representation for invariance and music classification. ICASSP 2014: 6984-6988 - [c23]Chiyuan Zhang, Stephen Voinea, Georgios Evangelopoulos, Lorenzo Rosasco, Tomaso A. Poggio:
Phone classification by a hierarchy of invariant representation layers. INTERSPEECH 2014: 2346-2350 - [c22]Stephen Voinea, Chiyuan Zhang, Georgios Evangelopoulos, Lorenzo Rosasco, Tomaso A. Poggio:
Word-level invariant representations from acoustic waveforms. INTERSPEECH 2014: 2385-2389 - [c21]Carlo Ciliberto, Luca Fiorio, Marco Maggiali, Lorenzo Natale, Lorenzo Rosasco, Giorgio Metta, Giulio Sandini, Francesco Nori:
Exploiting global force torque measurements for local compliance estimation in tactile arrays. IROS 2014: 3994-3999 - [c20]Youssef Mroueh, Lorenzo Rosasco:
On efficiency and low sample complexity in phase retrieval. ISIT 2014: 931-935 - [i17]Chiyuan Zhang, Georgios Evangelopoulos, Stephen Voinea, Lorenzo Rosasco, Tomaso A. Poggio:
A Deep Representation for Invariance And Music Classification. CoRR abs/1404.0400 (2014) - [i16]Lorenzo Rosasco, Andrea Tacchetti, Silvia Villa:
Regularization by Early Stopping for Online Learning Algorithms. CoRR abs/1405.0042 (2014) - [i15]Georgios Evangelopoulos, Stephen Voinea, Chiyuan Zhang, Lorenzo Rosasco, Tomaso A. Poggio:
Learning An Invariant Speech Representation. CoRR abs/1406.3884 (2014) - 2013
- [j14]Lorenzo Rosasco, Silvia Villa, Sofia Mosci, Matteo Santoro, Alessandro Verri:
Nonparametric sparsity and regularization. J. Mach. Learn. Res. 14(1): 1665-1714 (2013) - [j13]Andrea Tacchetti, Pavan Kumar Mallapragada, Matteo Santoro, Lorenzo Rosasco:
GURLS: a least squares library for supervised learning. J. Mach. Learn. Res. 14(1): 3201-3205 (2013) - [c19]Silvia Villa, Lorenzo Rosasco, Tomaso A. Poggio:
On Learnability, Complexity and Stability. Empirical Inference 2013: 59-69 - [c18]Sean Ryan Fanello, Carlo Ciliberto, Matteo Santoro, Lorenzo Natale, Giorgio Metta, Lorenzo Rosasco, Francesca Odone:
iCub World: Friendly Robots Help Building Good Vision Data-Sets. CVPR Workshops 2013: 700-705 - [c17]Carlo Ciliberto, Sean Ryan Fanello, Matteo Santoro, Lorenzo Natale, Giorgio Metta, Lorenzo Rosasco:
On the impact of learning hierarchical representations for visual recognition in robotics. IROS 2013: 3759-3764 - [c16]Alessandro Rudi, Guillermo D. Cañas, Lorenzo Rosasco:
On the Sample Complexity of Subspace Learning. NIPS 2013: 2067-2075 - [i14]Youssef Mroueh, Lorenzo Rosasco:
q-ary Compressive Sensing. CoRR abs/1302.5168 (2013) - [i13]Andrea Tacchetti, Pavan Kumar Mallapragada, Matteo Santoro, Lorenzo Rosasco:
GURLS: a Least Squares Library for Supervised Learning. CoRR abs/1303.0934 (2013) - [i12]Silvia Villa, Lorenzo Rosasco, Tomaso A. Poggio:
On Learnability, Complexity and Stability. CoRR abs/1303.5976 (2013) - [i11]Sean Ryan Fanello, Carlo Ciliberto, Matteo Santoro, Lorenzo Natale, Giorgio Metta, Lorenzo Rosasco, Francesca Odone:
iCub World: Friendly Robots Help Building Good Vision Data-Sets. CoRR abs/1306.3560 (2013) - [i10]Fabio Anselmi, Joel Z. Leibo, Lorenzo Rosasco, Jim Mutch, Andrea Tacchetti, Tomaso A. Poggio:
Unsupervised Learning of Invariant Representations in Hierarchical Architectures. CoRR abs/1311.4158 (2013) - [i9]Youssef Mroueh, Lorenzo Rosasco:
Quantization and Greed are Good: One bit Phase Retrieval, Robustness and Greedy Refinements. CoRR abs/1312.1830 (2013) - 2012
- [j12]Mauricio A. Álvarez, Lorenzo Rosasco, Neil D. Lawrence:
Kernels for Vector-Valued Functions: A Review. Found. Trends Mach. Learn. 4(3): 195-266 (2012) - [j11]Luca Baldassarre, Lorenzo Rosasco, Annalisa Barla, Alessandro Verri:
Multi-output learning via spectral filtering. Mach. Learn. 87(3): 259-301 (2012) - [c15]Guillermo D. Cañas, Tomaso A. Poggio, Lorenzo Rosasco:
Learning Manifolds with K-Means and K-Flats. NIPS 2012: 2474-2482 - [c14]Guillermo D. Cañas, Lorenzo Rosasco:
Learning Probability Measures with respect to Optimal Transport Metrics. NIPS 2012: 2501-2509 - [c13]Youssef Mroueh, Tomaso A. Poggio, Lorenzo Rosasco, Jean-Jacques E. Slotine:
Multiclass Learning with Simplex Coding. NIPS 2012: 2798-2806 - [i8]Lorenzo Rosasco, Silvia Villa, Sofia Mosci, Matteo Santoro, Alessandro Verri:
Nonparametric sparsity and regularization. CoRR abs/1208.2572 (2012) - [i7]Silvia Villa, Lorenzo Rosasco, Sofia Mosci, Alessandro Verri:
Proximal methods for the latent group lasso penalty. CoRR abs/1209.0368 (2012) - [i6]Guillermo D. Cañas, Lorenzo Rosasco:
Learning Probability Measures with respect to Optimal Transport Metrics. CoRR abs/1209.1077 (2012) - [i5]Guillermo D. Cañas, Tomaso A. Poggio, Lorenzo Rosasco:
Learning Manifolds with K-Means and K-Flats. CoRR abs/1209.1121 (2012) - [i4]Youssef Mroueh, Tomaso A. Poggio, Lorenzo Rosasco, Jean-Jacques E. Slotine:
Multiclass Learning with Simplex Coding. CoRR abs/1209.1360 (2012) - 2011
- [i3]Tomaso A. Poggio, Stephen Voinea, Lorenzo Rosasco:
Online Learning, Stability, and Stochastic Gradient Descent. CoRR abs/1105.4701 (2011) - [i2]Mauricio A. Álvarez, Lorenzo Rosasco, Neil D. Lawrence:
Kernels for Vector-Valued Functions: a Review. CoRR abs/1106.6251 (2011) - [i1]Matthias Hein, Gábor Lugosi, Lorenzo Rosasco, Steve Smale:
Mathematical and Computational Foundations of Learning Theory (Dagstuhl Seminar 11291). Dagstuhl Reports 1(7): 53-69 (2011) - 2010
- [j10]Steve Smale, Lorenzo Rosasco, Jake V. Bouvrie, Andrea Caponnetto, Tomaso A. Poggio:
Mathematics of the Neural Response. Found. Comput. Math. 10(1): 67-91 (2010) - [j9]Ernesto De Vito, Sergei V. Pereverzyev, Lorenzo Rosasco:
Adaptive Kernel Methods Using the Balancing Principle. Found. Comput. Math. 10(4): 455-479 (2010) - [j8]Lorenzo Rosasco, Mikhail Belkin, Ernesto De Vito:
On Learning with Integral Operators. J. Mach. Learn. Res. 11: 905-934 (2010) - [c12]Ernesto De Vito, Lorenzo Rosasco, Alessandro Toigo:
Spectral Regularization for Support Estimation. NIPS 2010: 487-495 - [c11]Sofia Mosci, Silvia Villa, Alessandro Verri, Lorenzo Rosasco:
A Primal-Dual Algorithm for Group Sparse Regularization with Overlapping Groups. NIPS 2010: 2604-2612 - [c10]Luca Baldassarre, Lorenzo Rosasco, Annalisa Barla, Alessandro Verri:
Vector Field Learning via Spectral Filtering. ECML/PKDD (1) 2010: 56-71 - [c9]Sofia Mosci, Lorenzo Rosasco, Matteo Santoro, Alessandro Verri, Silvia Villa:
Solving Structured Sparsity Regularization with Proximal Methods. ECML/PKDD (2) 2010: 418-433 - [c8]Lorenzo Rosasco, Matteo Santoro, Sofia Mosci, Alessandro Verri, Silvia Villa:
A Regularization Approach to Nonlinear Variable Selection. AISTATS 2010: 653-660
2000 – 2009
- 2009
- [j7]Christine De Mol, Ernesto De Vito, Lorenzo Rosasco:
Elastic-net regularization in learning theory. J. Complex. 25(2): 201-230 (2009) - [c7]Lorenzo Rosasco, Mikhail Belkin, Ernesto De Vito:
A Note on Learning with Integral Operators. COLT 2009 - [c6]Nicoletta Noceti, Barbara Caputo, Claudio Castellini, Luca Baldassarre, Annalisa Barla, Lorenzo Rosasco, Francesca Odone, Giulio Sandini:
Towards a Theoretical Framework for Learning Multi-modal Patterns for Embodied Agents. ICIAP 2009: 239-248 - [c5]Jake V. Bouvrie, Lorenzo Rosasco, Tomaso A. Poggio:
On Invariance in Hierarchical Models. NIPS 2009: 162-170 - 2008
- [j6]L. Lo Gerfo, Lorenzo Rosasco, Francesca Odone, Ernesto De Vito, Alessandro Verri:
Spectral Algorithms for Supervised Learning. Neural Comput. 20(7): 1873-1897 (2008) - [c4]Annalisa Barla, Sofia Mosci, Lorenzo Rosasco, Alessandro Verri:
A method for robust variable selection with significance assessment. ESANN 2008: 83-88 - 2007
- [j5]Frank Bauer, Sergei V. Pereverzev, Lorenzo Rosasco:
On regularization algorithms in learning theory. J. Complex. 23(1): 52-72 (2007) - [c3]Sofia Mosci, Lorenzo Rosasco, Alessandro Verri:
Dimensionality reduction and generalization. ICML 2007: 657-664 - 2006
- [b1]Lorenzo Rosasco:
Regularization approaches in learning theory. University of Genoa, Italy, 2006 - 2005
- [j4]Ernesto De Vito, Andrea Caponnetto, Lorenzo Rosasco:
Model Selection for Regularized Least-Squares Algorithm in Learning Theory. Found. Comput. Math. 5(1): 59-85 (2005) - [j3]Ernesto De Vito, Lorenzo Rosasco, Andrea Caponnetto, Umberto De Giovannini, Francesca Odone:
Learning from Examples as an Inverse Problem. J. Mach. Learn. Res. 6: 883-904 (2005) - [c2]Andrea Caponnetto, Lorenzo Rosasco, Francesca Odone, Alessandro Verri:
Support vector algorithms as regularization networks. ESANN 2005: 595-600 - 2004
- [j2]Ernesto De Vito, Lorenzo Rosasco, Andrea Caponnetto, Michele Piana, Alessandro Verri:
Some Properties of Regularized Kernel Methods. J. Mach. Learn. Res. 5: 1363-1390 (2004) - [j1]Lorenzo Rosasco, Ernesto De Vito, Andrea Caponnetto, Michele Piana, Alessandro Verri:
Are Loss Functions All the Same?. Neural Comput. 16(5): 1063-107 (2004) - [c1]Lorenzo Rosasco, Andrea Caponnetto, Ernesto De Vito, Francesca Odone, Umberto De Giovannini:
Learning, Regularization and Ill-Posed Inverse Problems. NIPS 2004: 1145-1152
Coauthor Index
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