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Ruud JG van Sloun

2 accepted papers

2020

Deep probabilistic subsampling for task-adaptive compressed sensing

ICLR 2020poster

The field of deep learning is commonly concerned with optimizing predictive models using large pre-acquired datasets of densely sampled datapoints or signals. In this work, we demonstrate that the deep learning paradigm can be extended to incorporate a subsampling scheme that is jointly optimized un…

Cited by 52SourcecodeScholar
2020

ProxSGD: Training Structured Neural Networks under Regularization and Constraints

ICLR 2020poster

In this paper, we consider the problem of training neural networks (NN). To promote a NN with specific structures, we explicitly take into consideration the nonsmooth regularization (such as L1-norm) and constraints (such as interval constraint). This is formulated as a constrained nonsmooth nonconv…

Cited by 30SourceScholar