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ORCIDLorenzo Rosasco
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- affiliation: MIT, Cambridge, MA, USA
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2020 – today
- 2021
[i70]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)- 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 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 - [i69]Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi:
A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings. CoRR abs/2002.05424 (2020) - [i68]Cristian Rusu, Lorenzo Rosasco:
Constructing fast approximate eigenspaces with application to the fast graph Fourier transforms. CoRR abs/2002.09723 (2020) - [i67]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) - [i66]Gian Maria Marconi, Lorenzo Rosasco, Carlo Ciliberto:
Hyperbolic Manifold Regression. CoRR abs/2005.13885 (2020) - [i65]Cesare Molinari, Mathurin Massias, Lorenzo Rosasco, Silvia Villa:
Implicit regularization for convex regularizers. CoRR abs/2006.09859 (2020) - [i64]Nicolò Pagliana, Alessandro Rudi, Ernesto De Vito, Lorenzo Rosasco:
Interpolation and Learning with Scale Dependent Kernels. CoRR abs/2006.09984 (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 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 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 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 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]