Structured sparsity regularization is a class of methods, and an area of research in statistical learning theory, that extend and generalize sparsityâ€¦Â (More)

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2016

2016

- Pei Yang, Jingrui He
- 2016 IEEE 16th International Conference on Dataâ€¦
- 2016

Motivated by real applications, heterogeneous learning has emerged as an important research area, which aims to model the coâ€¦Â (More)

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2013

2013

- Hyon-Jung Kim, Esa Ollila, Visa Koivunen
- 2013 IEEE International Conference on Acousticsâ€¦
- 2013

Multi-linear techniques using tensor decompositions provide a unifying framework for the high-dimensional data analysis. Sparsityâ€¦Â (More)

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Review

2012

Review

2012

This paper reviews our recent work on the application of a class of techniques known as ADMM (alternating direction method ofâ€¦Â (More)

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2011

2011

- Rodolphe Jenatton, Alexandre Gramfort, Vincent Michel, Guillaume Obozinski, Francis R. Bach, Bertrand Thirion
- 2011 International Workshop on Patternâ€¦
- 2011

Inverse inference, or "brain reading", is a recent paradigm for analyzing functional magnetic resonance imaging (fMRI) dataâ€¦Â (More)

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Highly Cited

2010

Highly Cited

2010

- Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach
- AISTATS
- 2010

We present an extension of sparse PCA, or sparse dictionary learning, where the sparsity patterns of all dictionary elements areâ€¦Â (More)

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2010

2010

- Sofia Mosci, Lorenzo Rosasco, Matteo Santoro, Alessandro Verri, Silvia Villa
- ECML/PKDD
- 2010

Proximal methods have recently been shown to provide effective optimization procedures to solve the variational problems definingâ€¦Â (More)

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Highly Cited

2010

Highly Cited

2010

- Seyoung Kim, Eric P. Xing
- ICML
- 2010

We consider the problem of learning a sparse multi-task regression, where the structure in the outputs can be represented as aâ€¦Â (More)

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Highly Cited

2010

Highly Cited

2010

- Jun Liu, Jieping Ye
- NIPS
- 2010

We consider the tree structured group Lasso where the structure over the features can be represented as a tree with leaf nodes asâ€¦Â (More)

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2009

2009

In this paper we propose a general framework to characterize and solve the optimization problems underlying a large class ofâ€¦Â (More)

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2009

2009

- Seyoung Kim, Eric P. Xing
- 2009

We consider the problem of learning a sparse multi-task regression with an application to a genetic association mapping problemâ€¦Â (More)

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