An interior-point stochastic approximation method and an L1-regularized delta rule

NeurIPS 2008 Peter CarbonettoMark SchmidtNando D. Freitas

The stochastic approximation method is behind the solution to many important, actively-studied problems in machine learning. Despite its far-reaching application, there is almost no work on applying stochastic approximation to learning problems with constraints... (read more)

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