{"id":"W2127300249","doi":"10.1109/tit.2009.2016018","title":"Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\\ell _{1}$-Constrained Quadratic Programming (Lasso)","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Information Theory","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":1252,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Alfred P. Sloan Foundation","keywords":"Lasso (programming language); Compressed sensing; Dimension (graph theory); Algorithm; Mathematics; Quadratic programming; Quadratic equation; Gaussian; Combinatorics; Noise (video); Computer science; Applied mathematics; Discrete mathematics; Mathematical optimization; Artificial intelligence; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null}