Sketch Fewer to Recognize More by Learning a Co-Regularized Sparse Representation
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2019.2963862
Abstract: Categorizing free-hand human sketches has profound implications in applications such as human computer interaction and image retrieval. The task is non-trivial due to the iconic nature of sketches, signified by large variances in both appearance… read more here.
Keywords: fewer recognize; sketch; regularized sparse; sparse representation ... See more keywords
Regularized sparse decomposition model for speech enhancement via convex distortion measure
Sign Up to like & getrecommendations! Published in 2018 at "Modern Physics Letters B"
DOI: 10.1142/s0217984918502627
Abstract: An important stage in speech enhancement is to estimate noise signal which is a difficult task in non-stationary and low signal-to-noise conditions. This paper presents an iterative speech enhancem... read more here.
Keywords: decomposition model; regularized sparse; speech; speech enhancement ... See more keywords
Federated Optimization of ℓ0-norm Regularized Sparse Learning
Sign Up to like & getrecommendations! Published in 2022 at "Algorithms"
DOI: 10.3390/a15090319
Abstract: Regularized sparse learning with the ℓ0-norm is important in many areas, including statistical learning and signal processing. Iterative hard thresholding (IHT) methods are the state-of-the-art for nonconvex-constrained sparse learning due to their capability of recovering… read more here.
Keywords: regularized sparse; federated optimization; hard thresholding; sparse learning ... See more keywords