arXiv (Cornell University) · 2020 · 10 citations · 14 references
ComputingComputer ScienceMathematicsData MiningMachine LearningStatistical ModelingDimension ReductionDimensionality ReductionOptimization For Machine LearningPattern RecognitionRepresentation LearningGradient DescentLinear ModelsPruningSparse Feature DetectionSparse Feature RepresentationSparse LearningSparse ModelsSparsity Induction
We analyse the pruning procedure behind the lottery ticket hypothesis arXiv:1803.03635v5, iterative magnitude pruning (IMP), when applied to linear models trained by gradient flow. We begin by presenting sufficient conditions on the statistical structure of the features under which IMP prunes those features that have smallest projection onto the data. Following this, we explore IMP as a method for sparse estimation.
14
Adam: A Method for Stochastic Optimization
Diederik P. Kingma, Jimmy Ba · UvA-DARE (University of Amsterdam) · 2014 · 84.8K citations · Full text
Ideal spatial adaptation by wavelet shrinkage
David L. Donoho, Iain M. Johnstone · Biometrika · 1994 · 7.8K citations