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Found 4 papers, 1 papers with code
Testing Stationarity Concepts for ReLU Networks: Hardness, Regularity, and Robust Algorithms
This implies that testing a certain stationarity concept for a modern nonsmooth neural network is in general computationally intractable.
Practical Schemes for Finding Near-Stationary Points of Convex Finite-Sums
In convex optimization, the problem of finding near-stationary points has not been adequately studied yet, unlike other optimality measures such as the function value.
Learning Feature Sparse Principal Subspace
This paper presents new algorithms to solve the feature-sparsity constrained PCA problem (FSPCA), which performs feature selection and PCA simultaneously.
Learning Feature Sparse Principal Components
This paper presents new algorithms to solve the feature-sparsity constrained PCA problem (FSPCA), which performs feature selection and PCA simultaneously.
