Lorenzo Rosasco

发表

Statistical and Computational Trade-Offs in Kernel K-Means

Daniele Calandriello, Lorenzo Rosasco, L. Rosasco, 2019, NeurIPS.

Kernel methods through the roof: handling billions of points efficiently pdf

Lorenzo Rosasco, Giacomo Meanti, Luigi Carratino, 2020, NeurIPS.

Theory I: Why and When Can Deep Networks Avoid the Curse of Dimensionality?

Lorenzo Rosasco, Tomaso Poggio, Hrushikesh Narhar Mhaskar, 2016 .

Spectral Algorithms for Supervised Learning

Lorenzo Rosasco, Francesca Odone, Alessandro Verri, 2008, Neural Computation.

Are Loss Functions All the Same?

Lorenzo Rosasco, Alessandro Verri, Ernesto De Vito, 2004, Neural Computation.

Learning, Regularization and Ill-Posed Inverse Problems

Lorenzo Rosasco, Francesca Odone, Ernesto De Vito, 2004, NIPS.

Support vector algorithms as regularization networks

Lorenzo Rosasco, Francesca Odone, Alessandro Verri, 2005, ESANN.

Notes on the Shannon Entropy of the Neural Response

Lorenzo Rosasco, Steve Smale, Greg Shakhnarovich, 2009 .

Why and when can deep-but not shallow-networks avoid the curse of dimensionality: A review

Lorenzo Rosasco, Tomaso A. Poggio, Brando Miranda, 2016, International Journal of Automation and Computing.

Faster Kriging: Facing High-Dimensional Simulators

Emanuele Borgonovo, Lorenzo Rosasco, Alessandro Rudi, 2020, Oper. Res..

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

Lorenzo Rosasco, Elisa Maiettini, Raffaello Camoriano, 2020, ArXiv.

Notes on Hierarchical Splines, DCLNs and i-theory

Tomaso Poggio, Lorenzo Rosasco, Amnon Shashua, 2015 .

Theory of Deep Learning III: explaining the non-overfitting puzzle pdf

Lorenzo Rosasco, Tomaso A. Poggio, Kenji Kawaguchi, 2017, ArXiv.

Supplementary Material for NIPS 2009 Paper #978, "On Invariance in Hierarchical Models"

Lorenzo Rosasco, Tomaso Poggio, Jake Bouvrie, 2009 .

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

Lorenzo Rosasco, Cristian Rusu, 2020, ArXiv.

Optimal rates for spectral algorithms with least-squares regression over Hilbert spaces

Volkan Cevher, Lorenzo Rosasco, Alessandro Rudi, 2018, Applied and Computational Harmonic Analysis.

Optimal Learning for Multi-pass Stochastic Gradient Methods

Lorenzo Rosasco, Junhong Lin, L. Rosasco, 2016, NIPS.

GURLS: a Toolbox for Regularized Least Squares Learning

Lorenzo Rosasco, Andrea Tacchetti, Matteo Santoro, 2012 .

A method for robust variable selection with significance assessment

Lorenzo Rosasco, Annalisa Barla, Alessandro Verri, 2008, ESANN.

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

Lorenzo Rosasco, Alessandro Rudi, Nicholas Sterge, 2019, ArXiv.

Incremental semiparametric inverse dynamics learning

Giorgio Metta, Lorenzo Rosasco, Francesco Nori, 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).

I-theory on depth vs width: hierarchical function composition

Tomaso Poggio, Lorenzo Rosasco, Fabio Anselmi, 2015 .

iCubWorld Transformations - Full Images - 15x10 - Parts 1a and 1b

Lorenzo Rosasco, Lorenzo Natale, Carlo Ciliberto, 2016 .

NYTRO: When Subsampling Meets Early Stopping

Lorenzo Rosasco, Alessandro Rudi, Raffaello Camoriano, 2015, AISTATS.

Deep Convolutional Networks are Hierarchical Kernel Machines pdf

Lorenzo Rosasco, Tomaso A. Poggio, Cheston Tan, 2015, ArXiv.

Exploiting global force torque measurements for local compliance estimation in tactile arrays

Giulio Sandini, Giorgio Metta, Lorenzo Rosasco, 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

iCub World: Friendly Robots Help Building Good Vision Data-Sets

Giorgio Metta, Lorenzo Rosasco, Lorenzo Natale, 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops.

Generalization Properties and Implicit Regularization for Multiple Passes SGM

Lorenzo Rosasco, Junhong Lin, Raffaello Camoriano, 2016, ICML.

On Invariance in Hierarchical Models

Lorenzo Rosasco, Tomaso A. Poggio, Jake V. Bouvrie, 2009, NIPS.

Adaptive Kernel Methods Using the Balancing Principle

Lorenzo Rosasco, Ernesto De Vito, Sergei V. Pereverzyev, 2010, Found. Comput. Math..

Convex Learning of Multiple Tasks and their Structure

Lorenzo Rosasco, Tomaso A. Poggio, Carlo Ciliberto, 2015, ICML.

A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings pdf

Lorenzo Rosasco, Alessandro Rudi, Carlo Ciliberto, 2020, J. Mach. Learn. Res..

On Learning with Integral Operators

Mikhail Belkin, Lorenzo Rosasco, Ernesto De Vito, 2010, J. Mach. Learn. Res..

Sparse Multiple Kernel Learning: Support Identification via Mirror Stratifiability

Lorenzo Rosasco, Silvia Villa, Guillaume Garrigos, 2018, 2018 26th European Signal Processing Conference (EUSIPCO).

Spectral Regularization for Support Estimation

Lorenzo Rosasco, Ernesto De Vito, Alessandro Toigo, 2010, NIPS.

On the Sample Complexity of Subspace Learning

Lorenzo Rosasco, Alessandro Rudi, Guillermo D. Cañas, 2013, NIPS.

iCubWorld Transformations - Full Images - 15x10 - Parts 2a and 2b

Lorenzo Rosasco, Lorenzo Natale, Carlo Ciliberto, 2016 .

Iterative Regularization for Learning with Convex Loss Functions

Lorenzo Rosasco, Ding-Xuan Zhou, Junhong Lin, 2015, J. Mach. Learn. Res..

Are we Done with Object Recognition? The iCub robot's Perspective

Lorenzo Rosasco, Lorenzo Natale, Francesca Odone, 2017, Robotics Auton. Syst..

Incremental Object Recognition in Robotics with Extension to New Classes in Constant Time pdf

Giorgio Metta, Lorenzo Rosasco, Lorenzo Natale, 2016, ArXiv.

Iterative regularization for convex regularizers

Lorenzo Rosasco, Silvia Villa, Mathurin Massias, 2020, AISTATS.

Vector Field Learning via Spectral Filtering

Lorenzo Rosasco, Luca Baldassarre, Annalisa Barla, 2010, ECML/PKDD.

Interactive data collection for deep learning object detectors on humanoid robots

Lorenzo Rosasco, Lorenzo Natale, Giulia Pasquale, 2017, 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids).

Learning An Invariant Speech Representation pdf

Lorenzo Rosasco, Tomaso A. Poggio, Stephen Voinea, 2014, ArXiv.

A Regularization Approach to Nonlinear Variable Selection

Lorenzo Rosasco, Alessandro Verri, Silvia Villa, 2010, AISTATS.

Quantization and Greed are Good: One bit Phase Retrieval, Robustness and Greedy Refinements pdf

Lorenzo Rosasco, Youssef Mroueh, L. Rosasco, 2013, ArXiv.

Elastic-net regularization in learning theory

Lorenzo Rosasco, Ernesto De Vito, Christine De Mol, 2008, J. Complex..

Generalization Properties of Doubly Online Learning Algorithms

Lorenzo Rosasco, Junhong Lin, 2018, J. Complex..

Constrained DMPs for Feasible Skill Learning on Humanoid Robots

Daniele Pucci, Daniele Calandriello, Lorenzo Rosasco, 2018, 2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids).

Mathematical and Computational Foundations of Learning Theory (Dagstuhl Seminar 15361)

Matthias Hein, Lorenzo Rosasco, Gábor Lugosi, 2015, Dagstuhl Reports.

A deep representation for invariance and music classification

Lorenzo Rosasco, Tomaso A. Poggio, Stephen Voinea, 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Symmetry-adapted representation learning

Lorenzo Rosasco, Tomaso A. Poggio, Georgios Evangelopoulos, 2019, Pattern Recognit..

Phone classification by a hierarchy of invariant representation layers

Lorenzo Rosasco, Tomaso A. Poggio, Stephen Voinea, 2014, INTERSPEECH.

Speeding-Up Object Detection Training for Robotics with FALKON

Lorenzo Rosasco, Lorenzo Natale, Giulia Pasquale, 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Hyperbolic Manifold Regression

Lorenzo Rosasco, Carlo Ciliberto, Gian Maria Marconi, 2020, AISTATS.

Multi-Scale Vector Quantization with Reconstruction Trees pdf

Lorenzo Rosasco, Enrico Cecini, Ernesto De Vito, 2019, Information and Inference: A Journal of the IMA.

Some Properties of Regularized Kernel Methods

Lorenzo Rosasco, Alessandro Verri, Ernesto De Vito, 2004, J. Mach. Learn. Res..

Word-level invariant representations from acoustic waveforms

Lorenzo Rosasco, Tomaso A. Poggio, Stephen Voinea, 2014, INTERSPEECH.

On efficiency and low sample complexity in phase retrieval

Lorenzo Rosasco, Youssef Mroueh, L. Rosasco, 2014, 2014 IEEE International Symposium on Information Theory.

Learning with SGD and Random Features

Lorenzo Rosasco, Luigi Carratino, Alessandro Rudi, 2018, NeurIPS.

iCubWorld Transformations - 256x256

Lorenzo Rosasco, Lorenzo Natale, Carlo Ciliberto, 2016 .

Solving lp-norm regularization with tensor kernels

Lorenzo Rosasco, Saverio Salzo, Johan Suykens, 2018, AISTATS.

Multi-output learning via spectral filtering

Lorenzo Rosasco, Luca Baldassarre, Annalisa Barla, 2012, Machine Learning.

Unsupervised learning of invariant representations with low sample complexity: the magic of sensory cortex or a new framework for machine learning?

Tomaso Poggio, Lorenzo Rosasco, Joel Z. Leibo, 2013, 1311.4158.

q-ary Compressive Sensing pdf

Lorenzo Rosasco, Youssef Mroueh, 2013, ArXiv.

Teaching Robots to Learn New Objects in Constant Time

Giorgio Metta, Lorenzo Rosasco, Lorenzo Natale, 2016 .

Modified Fejér sequences and applications

Lorenzo Rosasco, Silvia Villa, Ding-Xuan Zhou, 2015, Comput. Optim. Appl..

Towards a Theoretical Framework for Learning Multi-modal Patterns for Embodied Agents

Giulio Sandini, Barbara Caputo, Lorenzo Rosasco, 2009, ICIAP.

A Primal-Dual Algorithm for Group Sparse Regularization with Overlapping Groups

Lorenzo Rosasco, Alessandro Verri, Silvia Villa, 2010, NIPS.

Learning multiple visual tasks while discovering their structure

Lorenzo Rosasco, Carlo Ciliberto, Silvia Villa, 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Discovering discrete subword units with binarized autoencoders and hidden-Markov-model encoders

Lorenzo Rosasco, Leonardo Badino, Alessio Mereta, 2015, INTERSPEECH.

The computational magic of the ventral stream: sketch of a theory (and why some deep architectures work).

Lorenzo Rosasco, Joel Z. Leibo, Tomaso Poggio, 2012 .

Stochastic Forward–Backward Splitting for Monotone Inclusions

Lorenzo Rosasco, Bang Công Vu, Silvia Villa, 2016, J. Optim. Theory Appl..

Online Learning, Stability, and Stochastic Gradient Descent pdf

Lorenzo Rosasco, Tomaso A. Poggio, Stephen Voinea, 2011, ArXiv.

Learning from Examples as an Inverse Problem

Lorenzo Rosasco, Francesca Odone, Ernesto De Vito, 2005, J. Mach. Learn. Res..

FALKON: An Optimal Large Scale Kernel Method

Lorenzo Rosasco, Luigi Carratino, Alessandro Rudi, 2017, NIPS.

On Learnability, Complexity and Stability pdf

Lorenzo Rosasco, Tomaso A. Poggio, Silvia Villa, 2013, Empirical Inference.

Learning Manifolds with K-Means and K-Flats

Lorenzo Rosasco, Tomaso A. Poggio, Guillermo D. Cañas, 2012, NIPS.

Optimal Rates for Multi-pass Stochastic Gradient Methods

Lorenzo Rosasco, Junhong Lin, L. Rosasco, 2016, J. Mach. Learn. Res..

Genuine Personality Recognition from Highly Constrained Face Images

Lorenzo Rosasco, Nicoletta Noceti, Robert Ward, 2019, ICIAP.

Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification

Lorenzo Rosasco, Maurizio Filippone, Pietro Michiardi, 2018, NeurIPS.

Don't relax: early stopping for convex regularization pdf

Lorenzo Rosasco, Silvia Villa, Simon Matet, 2017, ArXiv.

Unsupervised learning of invariant representations

Lorenzo Rosasco, Joel Z. Leibo, Tomaso A. Poggio, 2016, Theor. Comput. Sci..

A Consistent Regularization Approach for Structured Prediction

Lorenzo Rosasco, Alessandro Rudi, Carlo Ciliberto, 2016, NIPS.

Unsupervised learning of invariant representations with low sample complexity: the magic of sensory cortex or a new framework for machine learning? pdf

Lorenzo Rosasco, Joel Z. Leibo, Tomaso A. Poggio, 2014 .

Combining sensory modalities and exploratory procedures to improve haptic object recognition in robotics

Lorenzo Rosasco, Lorenzo Natale, Carlo Ciliberto, 2016, 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids).

Neurally plausible mechanisms for learning selective and invariant representations

Lorenzo Rosasco, Fabio Anselmi, Ankit Patel, 2020, Journal of mathematical neuroscience.

Implicit Regularization of Accelerated Methods in Hilbert Spaces

Lorenzo Rosasco, Nicolo Pagliana, L. Rosasco, 2019, NeurIPS.

GURLS: a least squares library for supervised learning pdf

Lorenzo Rosasco, Andrea Tacchetti, Matteo Santoro, 2013, J. Mach. Learn. Res..

Generalization and Properties of the Neural Response

Andre Wibisono, Tomaso Poggio, Lorenzo Rosasco, 2010 .

On Invariance and Selectivity in Representation Learning pdf

Lorenzo Rosasco, Tomaso A. Poggio, Fabio Anselmi, 2015, ArXiv.

iCubWorld28 - Full Images

Lorenzo Rosasco, Lorenzo Natale, Francesca Odone, 2016 .

On regularization algorithms in learning theory

Lorenzo Rosasco, Sergei V. Pereverzyev, Frank Bauer, 2007, J. Complex..

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

Lorenzo Rosasco, Akshay Rangamani, Tomaso Poggio, 2020, ArXiv.

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

Daniele Calandriello, Lorenzo Rosasco, Luigi Carratino, 2020, ICML.

Enabling Depth-Driven Visual Attention on the iCub Humanoid Robot: Instructions for Use and New Perspectives pdf

Lorenzo Rosasco, Lorenzo Natale, Carlo Ciliberto, 2015, Front. Robot. AI.

Fast approximation of orthogonal matrices and application to PCA pdf

Lorenzo Rosasco, Cristian Rusu, L. Rosasco, 2019, Signal Process..

Iterate averaging as regularization for stochastic gradient descent

Lorenzo Rosasco, Gergely Neu, L. Rosasco, 2018, COLT.

Nonparametric sparsity and regularization pdf

Lorenzo Rosasco, Alessandro Verri, Silvia Villa, 2012, J. Mach. Learn. Res..

Mathematical and Computational Foundations of Learning Theory (Dagstuhl Seminar 11291)

Matthias Hein, Lorenzo Rosasco, Stephen Smale, 2011, Dagstuhl Reports.

Real-world Object Recognition with Off-the-shelf Deep Conv Nets: How Many Objects can iCub Learn? pdf

Lorenzo Rosasco, Lorenzo Natale, Francesca Odone, 2015, ArXiv.

Learning with Incremental Iterative Regularization

Lorenzo Rosasco, Silvia Villa, L. Rosasco, 2014, NIPS.

Less is More: Nyström Computational Regularization

Lorenzo Rosasco, Alessandro Rudi, Raffaello Camoriano, 2015, NIPS.

Characterizing the Input-Output Function of the Olfactory-Limbic Pathway in the Guinea Pig

Lorenzo Rosasco, Carlo Ciliberto, Michela Chiappalone, 2015, Comput. Intell. Neurosci..

Multiclass Learning with Simplex Coding

Lorenzo Rosasco, Tomaso A. Poggio, Jean-Jacques E. Slotine, 2012, NIPS.

iCubWorld Transformations - Full Images - 5x10

Lorenzo Rosasco, Lorenzo Natale, Carlo Ciliberto, 2016 .

Learning Probability Measures with respect to Optimal Transport Metrics

Lorenzo Rosasco, Guillermo D. Cañas, L. Rosasco, 2012, NIPS.

Optimal Rates for Learning with Nyström Stochastic Gradient Methods pdf

Lorenzo Rosasco, Junhong Lin, 2017, ArXiv.

Active perception: Building objects' models using tactile exploration

Lorenzo Rosasco, Lorenzo Natale, Nawid Jamali, 2016, 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids).

Holographic Embeddings of Knowledge Graphs

Lorenzo Rosasco, Tomaso A. Poggio, Maximilian Nickel, 2015, AAAI.

Gain with no Pain: Efficiency of Kernel-PCA by Nyström Sampling

Lorenzo Rosasco, Alessandro Rudi, Nicholas Sterge, 2020, AISTATS.

On-line object detection: a robotics challenge

Lorenzo Rosasco, Elisa Maiettini, Giulia Pasquale, 2019, Autonomous Robots.

Incremental robot learning of new objects with fixed update time

Giorgio Metta, Lorenzo Rosasco, Lorenzo Natale, 2016, 2017 IEEE International Conference on Robotics and Automation (ICRA).

Kernels for Vector-Valued Functions: a Review

Neil D. Lawrence, Lorenzo Rosasco, Mauricio A. Álvarez, 2011, Found. Trends Mach. Learn..

Proximal methods for the latent group lasso penalty

Lorenzo Rosasco, Alessandro Verri, Silvia Villa, 2012, Computational Optimization and Applications.

Solving Structured Sparsity Regularization with Proximal Methods

Lorenzo Rosasco, Alessandro Verri, Silvia Villa, 2010, ECML/PKDD.

Regularization by Early Stopping for Online Learning Algorithms pdf

Lorenzo Rosasco, Andrea Tacchetti, Silvia Villa, 2014, ArXiv.

Publisher Accessed Terms of Use Detailed Terms Mathematics of the Neural Response

Lorenzo Rosasco, Tomaso A. Poggio, Stephen Smale, 2022 .

Regularized ERM on random subspaces pdf

Lorenzo Rosasco, Andrea Della Vecchia, Ernesto De Vito, 2020, ArXiv.

Teaching iCub to recognize objects using deep Convolutional Neural Networks

Lorenzo Rosasco, Lorenzo Natale, Francesca Odone, 2015, MLIS@ICML.

Fast Region Proposal Learning for Object Detection for Robotics pdf

Lorenzo Rosasco, Elisa Maiettini, Giulia Pasquale, 2020, ArXiv.

Beating SGD Saturation with Tail-Averaging and Minibatching

Lorenzo Rosasco, Gergely Neu, Nicole Mücke, 2019, NeurIPS.

iCubWorld Transformations - Full Images - 15x10 - Part 3

Lorenzo Rosasco, Lorenzo Natale, Carlo Ciliberto, 2016 .

Fast Object Segmentation Learning with Kernel-based Methods for Robotics pdf

Lorenzo Rosasco, Elisa Maiettini, Giulia Pasquale, 2020, ArXiv.

On the impact of learning hierarchical representations for visual recognition in robotics

Giorgio Metta, Lorenzo Rosasco, Lorenzo Natale, 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Generalization Properties of Learning with Random Features

Lorenzo Rosasco, Alessandro Rudi, L. Rosasco, 2016, NIPS.

Regularization Predicts While Discovering Taxonomy

Tomaso Poggio, Lorenzo Rosasco, Youssef Mroueh, 2011 .

A Note on Learning with Integral Operators

Mikhail Belkin, Lorenzo Rosasco, Ernesto De Vito, 2009, COLT.

For interpolating kernel machines, minimizing the norm of the ERM solution minimizes stability.

Lorenzo Rosasco, Akshay Rangamani, Tomaso Poggio, 2020 .

Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret pdf

Daniele Calandriello, Lorenzo Rosasco, Luigi Carratino, 2019, COLT.

iCubWorld Transformations - IROS 2016 version

Lorenzo Rosasco, Lorenzo Natale, Carlo Ciliberto, 2016 .

Reproducing kernel Hilbert spaces on manifolds: Sobolev and Diffusion spaces pdf

Lorenzo Rosasco, Ernesto De Vito, Nicole Mücke, 2019, Analysis and Applications.

On Fast Leverage Score Sampling and Optimal Learning

Daniele Calandriello, Lorenzo Rosasco, Luigi Carratino, 2018, NeurIPS.

Learning to Avoid Obstacles With Minimal Intervention Control

Daniele Pucci, Daniele Calandriello, Lorenzo Rosasco, 2020, Frontiers in Robotics and AI.

Interpolation and Learning with Scale Dependent Kernels pdf

Lorenzo Rosasco, Alessandro Rudi, Nicolo Pagliana, 2020, ArXiv.

Implicit regularization for convex regularizers pdf

Lorenzo Rosasco, Silvia Villa, Mathurin Massias, 2020, ArXiv.

Manifold Structured Prediction

Lorenzo Rosasco, Alessandro Rudi, Carlo Ciliberto, 2018, NeurIPS.

Some Recent Advances in Multiscale Geometric Analysis of Point Clouds

Lorenzo Rosasco, Guangliang Chen, Mauro Maggioni, 2011 .

Theory III: Dynamics and Generalization in Deep Networks pdf

Lorenzo Rosasco, Tomaso A. Poggio, Brando Miranda, 2019, ArXiv.

Object identification from few examples by improving the invariance of a Deep Convolutional Neural Network

Lorenzo Rosasco, Carlo Ciliberto, Lorenzo Natale, 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Iterative Projection Methods for Structured Sparsity Regularization

Lorenzo Rosasco, Alessandro Verri, Silvia Villa, 2009 .

Dimensionality reduction and generalization

Lorenzo Rosasco, Alessandro Verri, Sofia Mosci, 2007, ICML '07.

Decentralised Learning with Random Features and Distributed Gradient Descent pdf

Lorenzo Rosasco, Patrick Rebeschini, Dominic Richards, 2020, ICML.

Consistent Multitask Learning with Nonlinear Output Relations

Lorenzo Rosasco, Alessandro Rudi, Massimiliano Pontil, 2017, NIPS.

Iterative Regularization via Dual Diagonal Descent

Lorenzo Rosasco, Silvia Villa, Guillaume Garrigos, 2016, Journal of Mathematical Imaging and Vision.

Model Selection for Regularized Least-Squares Algorithm in Learning Theory

Lorenzo Rosasco, Ernesto De Vito, Andrea Caponnetto, 2005, Found. Comput. Math..

Generalization Puzzles in Deep Networks

Lorenzo Rosasco, Brando Miranda, Qianli Liao, 2019 .

Discriminative template learning in group-convolutional networks for invariant speech representations

Lorenzo Rosasco, Tomaso A. Poggio, Stephen Voinea, 2015, INTERSPEECH.

From inexact optimization to learning via gradient concentration pdf

Lorenzo Rosasco, Nicole Mücke, Bernhard Stankewitz, 2021, Computational Optimization and Applications.

Accelerated Iterative Regularization via Dual Diagonal Descent

Lorenzo Rosasco, Silvia Villa, Luca Calatroni, 2019, SIAM J. Optim..

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

Daniele Calandriello, Lorenzo Rosasco, Luigi Carratino, 2021, ArXiv.

Iterative regularization for convex regularizers

Lorenzo Rosasco, Silvia Villa, Mathurin Massias, 2021, AISTATS.

Structured Prediction for CRiSP Inverse Kinematics Learning With Misspecified Robot Models

Lorenzo Rosasco, Carlo Ciliberto, Gian Maria Marconi, 2021, IEEE Robotics and Automation Letters.

Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression pdf

Lorenzo Rosasco, Giacomo Meanti, Luigi Carratino, 2022, AISTATS.

Understanding neural networks with reproducing kernel Banach spaces pdf

Lorenzo Rosasco, Stefano Vigogna, Francesca Bartolucci, 2021, ArXiv.

Constructing Fast Approximate Eigenspaces With Application to the Fast Graph Fourier Transforms

Lorenzo Rosasco, Cristian Rusu, L. Rosasco, 2020, IEEE Transactions on Signal Processing.

Fast Object Segmentation Learning with Kernel-based Methods for Robotics

Lorenzo Rosasco, Lorenzo Natale, Giulia Pasquale, 2020, 2021 IEEE International Conference on Robotics and Automation (ICRA).

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

Lorenzo Rosasco, Luigi Carratino, Silvia Villa, 2021, ArXiv.

Zeroth-order optimization with orthogonal random directions

Lorenzo Rosasco, Luis Tenorio, Silvia Villa, 2021, Mathematical Programming.

Asymptotics of Ridge(less) Regression under General Source Condition

Lorenzo Rosasco, Dominic Richards, Jaouad Mourtada, 2020, AISTATS.

On the Emergence of Whole-Body Strategies From Humanoid Robot Push-Recovery Learning

Daniele Pucci, Daniele Calandriello, Lorenzo Rosasco, 2021, IEEE Robotics and Automation Letters.

Thresholding gradient methods in Hilbert spaces: support identification and linear convergence

Lorenzo Rosasco, Silvia Villa, Guillaume Garrigos, 2017 .

UvA-DARE ( Digital Academic Repository ) A biology-driven approach identifies the hypoxia gene signature as a predictor of the outcome of neuroblastoma patients

Lorenzo Rosasco, Annalisa Barla, Alessandro Verri, 2010 .

Memo No . 35 August 5 , 2015 Deep Convolutional Networks are Hierarchical Kernel Machines

Lorenzo Rosasco, Tomaso Poggio, Cheston Tan, 2015 .

A First-Order Stochastic Primal-Dual Algorithm with Correction Step

Lorenzo Rosasco, Silvia Villa, Bang Cong Vu, 2016, 1602.07872.

Memo No . 022 June 15 , 2014 Learning An Invariant Speech Representation by Georgios Evangelopoulos ?

Lorenzo Rosasco, Tomaso Poggio, Stephen Voinea, 2014 .

Analysis of Elastic-Net Regularization in Learning Theory

Lorenzo Rosasco, Christine De Mol, Ernesto De Vito, 2008 .

Manifold Regularization

Lorenzo Rosasco, Francesca Odone, L. Rosasco, 2007 .

Monte Carlo wavelets: a randomized approach to frame discretization

Lorenzo Rosasco, Stefano Vigogna, Valeriya Naumova, 2019, 2019 13th International conference on Sampling Theory and Applications (SampTA).

The l1-l2 regularization framework unmasks the hypoxia signature hidden in the transcriptome of a set of heterogeneous neuroblastoma cell lines

Lorenzo Rosasco, Annalisa Barla, Alessandro Verri, 2009, BMC Genomics.

Is there sparsity beyond additive models

Lorenzo Rosasco, Alessandro Verri, Silvia Villa, 2012 .