Massimiliano Pontil

Hane Aung

Nadia Bianchi-Berthouze

Proceedings of the 30th International Conference on Machine Learning, 2013

Sparse coding for multitask and transfer learning.

[BibT_eX]

[DOI]

Proceedings of the 30th International Conference on Machine Learning, 2013

Transfer learning to account for idiosyncrasy in face and body expressions.

[BibT_eX]

[DOI]

Min S. H. Aung

Nadia Bianchi-Berthouze

Amanda C. de C. Williams

Paul J. Watson

Proceedings of the 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, 2013

Excess risk bounds for multitask learning with trace norm regularization.

[BibT_eX]

[DOI]

Proceedings of the COLT 2013, 2013

On Sparsity Inducing Regularization Methods for Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

2012

Exploiting Unrelated Tasks in Multi-Task Learning.

[BibT_eX]

[DOI]

Nadia Berthouze

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Structured Sparsity and Generalization.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2012

A General Framework for Structured Sparsity via Proximal Optimization.

[BibT_eX]

[DOI]

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Conditional mean embeddings as regressors - supplementary

[BibT_eX]

[DOI]

CoRR, 2012

PSICOV: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments.

[BibT_eX]

[DOI]

Bioinform., 2012

Structured Sparsity Models for Brain Decoding from fMRI Data.

[BibT_eX]

[DOI]

Luca Baldassarre

Janaina Mourão Miranda

Proceedings of the Second International Workshop on Pattern Recognition in NeuroImaging, 2012

Optimal kernel choice for large-scale two-sample tests.

[BibT_eX]

[DOI]

Arthur Gretton

Bharath K. Sriperumbudur

Dino Sejdinovic

Heiko Strathmann

Sivaraman Balakrishnan

Kenji Fukumizu

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Conditional mean embeddings as regressors.

[BibT_eX]

[DOI]

Proceedings of the 29th International Conference on Machine Learning, 2012

Modelling transition dynamics in MDPs with RKHS embeddings.

[BibT_eX]

[DOI]

Proceedings of the 29th International Conference on Machine Learning, 2012

Structured sparsity regularization approach to the EEG inverse problem.

[BibT_eX]

[DOI]

Jair Montoya-Martínez

Antonio Artés-Rodríguez

Lars Kai Hansen

Proceedings of the 3rd International Workshop on Cognitive Information Processing, 2012

Transfer learning in a heterogeneous environment.

[BibT_eX]

[DOI]

Proceedings of the 3rd International Workshop on Cognitive Information Processing, 2012

2011

A tale of many cities: universal patterns in human urban mobility

[BibT_eX]

[DOI]

CoRR, 2011

Efficient First Order Methods for Linear Composite Regularizers

[BibT_eX]

[DOI]

CoRR, 2011

Exploiting Semantic Annotations for Clustering Geographic Areas and Users in Location-based Social Networks.

[BibT_eX]

[DOI]

Proceedings of the Social Mobile Web, 2011

An Empirical Study of Geographic User Activity Patterns in Foursquare.

[BibT_eX]

[DOI]

Proceedings of the Fifth International Conference on Weblogs and Social Media, 2011

2010

K -Dimensional Coding Schemes in Hilbert Spaces.

[BibT_eX]

[DOI]

Augusto Maurer

IEEE Trans. Inf. Theory, 2010

On Spectral Learning.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2010

A Family of Penalty Functions for Structured Sparsity.

[BibT_eX]

[DOI]

Jean Morales

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009

When Is There a Representer Theorem? Vector Versus Matrix Regularizers.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2009

Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods.

[BibT_eX]

[DOI]

BMC Bioinform., 2009

Entropy conditions for L r -convergence of empirical processes.

[BibT_eX]

[DOI]

Andrea Caponnetto

Ernesto De Vito

Adv. Comput. Math., 2009

Empirical Bernstein Bounds and Sample-Variance Penalization.

[BibT_eX]

[DOI]

Proceedings of the COLT 2009, 2009

Taking Advantage of Sparsity in Multi-Task Learning.

[BibT_eX]

[DOI]

Karim Lounici

Alexandre B. Tsybakov

Sara A. van de Geer

Proceedings of the COLT 2009, 2009

Machine Learning Techniques for Biometrics.

[BibT_eX]

[DOI]

Francesca Odone

Proceedings of the Handbook of Remote Biometrics, 2009

2008

Convex multi-task feature learning.

[BibT_eX]

[DOI]

Mach. Learn., 2008

Universal Multi-Task Kernels.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2008

Online Gradient Descent Learning Algorithms.

[BibT_eX]

[DOI]

Yiming Ying

Found. Comput. Math., 2008

An Algorithm for Transfer Learning in a Heterogeneous Environment.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

Fast Prediction on a Tree.

[BibT_eX]

[DOI]

Sergio Rojas Galeano

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Online Prediction on Large Diameter Graphs.

[BibT_eX]

[DOI]

Guy Lever

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Generalization Bounds for K-Dimensional Coding Schemes in Hilbert Spaces.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 19th International Conference, 2008

A Uniform Lower Error Bound for Half-Space Learning.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 19th International Conference, 2008

2007

Feature space perspectives for learning the kernel.

[BibT_eX]

[DOI]

Mach. Learn., 2007

A Spectral Regularization Framework for Multi-Task Structure Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006

Prediction on a Graph with a Perceptron.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Multi-Task Feature Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

A DC-programming algorithm for kernel selection.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2006

2005

Wide coverage natural language processing using kernel methods and neural networks for structured data.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2005

On Learning Vector-Valued Functions.

[BibT_eX]

[DOI]

Neural Comput., 2005

Learning the Kernel Function via Regularization.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2005

Learning Multiple Tasks with Kernel Methods.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2005

Stability of Randomized Learning Algorithms.

[BibT_eX]

[DOI]

André Elisseeff

J. Mach. Learn. Res., 2005

Combining Graph Laplacians for Semi-Supervised Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Online learning over graphs.

[BibT_eX]

[DOI]

Lisa Wainer

Proceedings of the Machine Learning, 2005

Learning Convex Combinations of Continuously Parameterized Basic Kernels.

[BibT_eX]

[DOI]

Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005

2004

New results on error correcting output codes of kernel machines.

[BibT_eX]

[DOI]

Andrea Passerini

Paolo Frasconi

IEEE Trans. Neural Networks, 2004

Leave One Out Error, Stability, and Generalization of Voting Combinations of Classifiers.

[BibT_eX]

[DOI]

André Elisseeff

Mach. Learn., 2004

Kernels for Multi--task Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Regularized multi--task learning.

[BibT_eX]

[DOI]

Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

A Function Representation for Learning in Banach Spaces.

[BibT_eX]

[DOI]

Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004

2003

Image Representations and Feature Selection for Multimedia Database Search.

[BibT_eX]

[DOI]

Constantine Papageorgiou

IEEE Trans. Knowl. Data Eng., 2003

Combining flat and structured representations for fingerprint classification with recursive neural networks and support vector machines.

[BibT_eX]

[DOI]

Pattern Recognit., 2003

Full-body person recognition system.

[BibT_eX]

[DOI]

Pattern Recognit., 2003

A note on different covering numbers in learning theory.

[BibT_eX]

[DOI]

J. Complex., 2003

On different ensembles of kernel machines.

[BibT_eX]

[DOI]

Proceedings of the 11th European Symposium on Artificial Neural Networks, 2003

Reproducing kernels and regularization methods in machine learning.

[BibT_eX]

[DOI]

Proceedings of the 11th European Symposium on Artificial Neural Networks, 2003

2002

A Short Review of Statistical Learning Theory.

[BibT_eX]

[DOI]

Proceedings of the Neural Nets, 13th Italian Workshop on Neural Nets, 2002

Learning Preference Relations from Data.

[BibT_eX]

[DOI]

Proceedings of the Neural Nets, 13th Italian Workshop on Neural Nets, 2002

Maintenance Training of Electric Power Facilities Using Object Recognition by SVM.

[BibT_eX]

[DOI]

Chikahito Nakajima

Proceedings of the Pattern Recognition with Support Vector Machines, 2002

Support Vector Machines with Clustering for Training with Very Large Datasets.

[BibT_eX]

[DOI]

Proceedings of the Methods and Applications of Artificial Intelligence, 2002

From Margins to Probabilities in Multiclass Learning Problems.

[BibT_eX]

Andrea Passerini

Paolo Frasconi

Proceedings of the 15th European Conference on Artificial Intelligence, 2002

A Simple Algorithm for Learning Stable Machines.

[BibT_eX]

Proceedings of the 15th European Conference on Artificial Intelligence, 2002

2001

Categorization by Learning and Combining Object Parts.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Component-based Face Detection.

[BibT_eX]

[DOI]

Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2001), 2001

Fingerprint Classification with Combinations of Support Vector Machines.

[BibT_eX]

[DOI]

Yuan Yao

Paolo Frasconi

Proceedings of the Audio- and Video-Based Biometric Person Authentication, 2001

A New Machine Learning Approach to Fingerprint Classification.

[BibT_eX]

[DOI]

Proceedings of the AI*IA 2001: Advances in Artificial Intelligence, 2001

Support Vector Machines: Theory and Applications.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Its Applications, Advanced Lectures, 2001

2000

Statistical Learning Theory: A Primer.

[BibT_eX]

[DOI]

Int. J. Comput. Vis., 2000

Regularization Networks and Support Vector Machines.

[BibT_eX]

[DOI]

Adv. Comput. Math., 2000

Feature Selection for SVMs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 13, 2000

People Recognition and Pose Estimation in Image Sequences.

[BibT_eX]

[DOI]

Chikahito Nakajima

Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

Object Recognition and Detection by a Combination of Support Vector Machine and Rotation Invariant Phase Only Correlation.

[BibT_eX]

[DOI]

Proceedings of the 15th International Conference on Pattern Recognition, 2000

Bounds on the Generalization Performance of Kernel Machine Ensembles.

[BibT_eX]

Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

On the Noise Model of Support Vector Machines Regression.

[BibT_eX]

[DOI]

Sayan Mukherjee

Federico Girosi

Proceedings of the Algorithmic Learning Theory, 11th International Conference, 2000

A Note on the Generalization Performance of Kernel Classifiers with Margin.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 11th International Conference, 2000

1999

From regression to classification in support vector machines.

[BibT_eX]

[DOI]

Ryan M. Rifkin

Proceedings of the 7th European Symposium on Artificial Neural Networks, 1999

Support vector machines vs multi-layer perceptrons in particle identification.

[BibT_eX]

[DOI]

Proceedings of the 7th European Symposium on Artificial Neural Networks, 1999

A Note on Support Vector Machine Degeneracy.

[BibT_eX]

[DOI]

Ryan M. Rifkin

Proceedings of the Algorithmic Learning Theory, 10th International Conference, 1999

On the Vgamma Dimension for Regression in Reproducing Kernel Hilbert Spaces.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 10th International Conference, 1999

1998

Support Vector Machines for 3D Object Recognition.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 1998

Properties of Support Vector Machines.

[BibT_eX]

[DOI]

Neural Comput., 1998

Recognizing 3-D Objects with Linear Support Vector Machines.

[BibT_eX]

[DOI]

Stefano Rogai

Proceedings of the Computer Vision, 1998

1997

Direct Aspect-Based 3D Object Recognition.

[BibT_eX]

[DOI]