Prof. Mark Schmidt – Faster Algorithms for Deep Learning?

Faster Algorithms for Deep Learning? The last 10 years have seen a revolution in stochastic gradient methods, with variance-reduced methods like SAG/SVRG provably achieving faster convergence rates than all previous methods. These methods give dramatic speedups in a variety of applications but have had virtually no impact to the practice of training deep models. We […]

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