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Due to their wide applicability, sparse and low-rank models have quickly become some of the most important tools for todays researchers in machine learning, statistics, optimization, bioinformatics, computer vision, as well as signal and image processing. With this 495 topics class, last offered Winter quarter of 2013, we aimed to quickly bring interested students andPARSED CONTENT
The site had the following in the homepage, "EECS 495 Sparse and Low-rank recovery problems in machine learning." I noticed that the web site stated " EECS 495 Sparse and Low-rank recovery problems in machine learning." They also stated " In addition to a well curated collection of reference materials, registered students received a draft of a forthcoming manuscript authored by the instructors on sparse and low rank models and algorithms to use as class notes. For a complete class syllabus, including list of topics to be covered, please click here. Leave a Reply Cancel reply."