A General Family of Stochastic Proximal Gradient Methods for Deep
Learning
Papers citing "A General Family of Stochastic Proximal Gradient Methods for Deep Learning"
8 / 8 papers shown
Title |
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 Training Structured Neural Networks Through Manifold Identification and
Variance ReductionInternational Conference on Learning Representations (ICLR), 2021 |
 Adaptive Group Lasso Neural Network Models for Functions of Few
Variables and Time-Dependent DataSampling Theory, Signal Processing, and Data Analysis (SAMPTA), 2021 |
 A Bregman Learning Framework for Sparse Neural NetworksJournal of machine learning research (JMLR), 2021 |
