Sparse regression using mixed norms

Hybrid representationsfor audiophonic signal…Hybrid representations for audiophonic signal encodingAn iterativethresholding algorithm…An iterative thresholding algorithm for linear inverse problems with a sparsity constraintSignal Recovery byProximal…Signal Recovery by Proximal Forward-Backward SplittingModel Selection andEstimation in Regressio…Model Selection and Estimation in Regression with Grouped VariablesRegularization andVariable Selection Via…Regularization and Variable Selection Via the Elastic NetMulti-framerepresentations in…Multi-frame representations in linear inverse problems with mixed multi-constraintsIterative thresholdingalgorithmsIterative thresholding algorithmsAn iterative algorithmfor nonlinear inverse…An iterative algorithm for nonlinear inverse problems with joint sparsity constraints in vector-valued regimes and an application to color image inpaintingSparsity andpersistence: mixed norm…Sparsity and persistence: mixed norms provide simple signal models with dependent coefficientsRecovery Algorithms forVector-Valued Data with…Recovery Algorithms for Vector-Valued Data with Joint Sparsity ConstraintsUnder-determined sourceseparation via…Under-determined source separation via mixed-norm regularized minimizationThe composite absolutepenalties family for…The composite absolute penalties family for grouped and hierarchical variable selectionStructured Sparsity:from Mixed Norms to…Structured Sparsity: from Mixed Norms to Structured ShrinkageMultiple indefinitekernel learning with…Multiple indefinite kernel learning with mixed norm regularizationBeyond the NarrowbandApproximation: Wideband…Beyond the Narrowband Approximation: Wideband Convex Methods for Under-Determined Reverberant Audio Source SeparationExclusive Lasso forMulti-task Feature…Exclusive Lasso for Multi-task Feature SelectionEfficient L1/Lq NormRegularizationEfficient L1/Lq Norm RegularizationMixed norms withoverlapping groups as…Mixed norms with overlapping groups as signal priorsellp-ellq Penalty forSparse Linear and Spars…ellp-ellq Penalty for Sparse Linear and Sparse Multiple Kernel Multitask LearningMixed-norm estimates forthe M/EEG inverse…Mixed-norm estimates for the M/EEG inverse problem using accelerated gradient methodsSocial Sparsity!Neighborhood Systems…Social Sparsity! Neighborhood Systems Enrich Structured Shrinkage OperatorsTranslation-InvariantShrinkage/Thresholding…Translation-Invariant Shrinkage/Thresholding of Group Sparse SignalsMultimodal MultipartLearning for Action…Multimodal Multipart Learning for Action Recognition in Depth VideosA Penalty FunctionPromoting Sparsity…A Penalty Function Promoting Sparsity Within and Across GroupsSparse regression usingmixed normsSparse regression using mixed normsEarlier referencesFocus paperCiting papersOlderNewer

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