Project
Team
Sierra
Overall Objectives
Scientific Foundations
Application Domains
Software
New Results
- Local Component Analysis
- Weakly Supervised Learning of Foreground-Background Segmentation using Masked RBMs
- Clusterpath: an algorithm for clustering using convex fusion penalties
- Convex and Network Flow Optimization for Structured Sparsity
- Multi-scale Mining of fMRI data with Hierarchical Structured Sparsity
- Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization
- Generalized Fast Approximate Energy Minimization via Graph Cuts: Alpha-Expansion Beta-Shrink Moves
- Hybrid Deterministic-Stochastic Methods for Data Fitting
- Multi-task regression using minimal penalties
- Ask the locals: multi-way local pooling for image recognition
- Trace Lasso: a trace norm regularization for correlated designs
- Shaping level sets through submodular functions
- Itakura-Saito Nonnegative Matrix Factorization with group sparsity
- Online algorithms for nonnegative matrix factorization with the Itakura-Saito divergence
- A Graph-matching Kernel for Object Categorization
- Group Lasso with Overlaps: the Latent Group Lasso approach
- Sparse Image Representation with Epitomes
- Dictionary Learning for Deblurring and Digital Zoom
- Robust linear least squares regression
- Semantic hierarchies for image annotation
- Deviations of Stochastic Bandit Regret
- Minimax Policies for Combinatorial Prediction Games
- Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning
Partnerships and Cooperations
Bibliography
Project
Team
Sierra
Overall Objectives
Scientific Foundations
Application Domains
Software
New Results
- Local Component Analysis
- Weakly Supervised Learning of Foreground-Background Segmentation using Masked RBMs
- Clusterpath: an algorithm for clustering using convex fusion penalties
- Convex and Network Flow Optimization for Structured Sparsity
- Multi-scale Mining of fMRI data with Hierarchical Structured Sparsity
- Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization
- Generalized Fast Approximate Energy Minimization via Graph Cuts: Alpha-Expansion Beta-Shrink Moves
- Hybrid Deterministic-Stochastic Methods for Data Fitting
- Multi-task regression using minimal penalties
- Ask the locals: multi-way local pooling for image recognition
- Trace Lasso: a trace norm regularization for correlated designs
- Shaping level sets through submodular functions
- Itakura-Saito Nonnegative Matrix Factorization with group sparsity
- Online algorithms for nonnegative matrix factorization with the Itakura-Saito divergence
- A Graph-matching Kernel for Object Categorization
- Group Lasso with Overlaps: the Latent Group Lasso approach
- Sparse Image Representation with Epitomes
- Dictionary Learning for Deblurring and Digital Zoom
- Robust linear least squares regression
- Semantic hierarchies for image annotation
- Deviations of Stochastic Bandit Regret
- Minimax Policies for Combinatorial Prediction Games
- Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning
Partnerships and Cooperations
Bibliography
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