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Learning efficient sparse and low rank models
Pablo Sprechmann, Alex M. Bronstein, Guillermo Sapiro
Parsimony, including sparsity and low rank, has been shown to successfully model data in numerous machine learning and signal processing tasks. Traditionally, such modeling approac…
Learning Robust Low-Rank Representations
Pablo Sprechmann, Alex M. Bronstein, Guillermo Sapiro
In this paper we present a comprehensive framework for learning robust low-rank representations by combining and extending recent ideas for learning fast sparse coding regressors w…
Learning Efficient Structured Sparse Models
Alex Bronstein, Pablo Sprechmann, Guillermo Sapiro
We present a comprehensive framework for structured sparse coding and modeling extending the recent ideas of using learnable fast regressors to approximate exact sparse codes. For…