Efcient Learning of Sparse Representations with an EnergyBased Model MarcAurelio Ranzato Christopher Poultney Sumit Chopra Yan n LeCun Courant Institute of Mathematical Sciences New York University N PDF document - DocSlides
nyuedu Abstract We describe a novel unsupervised method for learning sparse overcomplete fea tures The model uses a linear encoder and a linear decoder p receded by a spar sifying nonlinearity that turns a code vector into a quasi binary sparse code ID: 30054Embed code:
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