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Found 5 papers, 1 papers with code
Learning from few examples: Classifying sex from retinal images via deep learning
Here, we showcase results for the performance of DL on small datasets to classify patient sex from fundus images - a trait thought not to be present or quantifiable in fundus images until recently.
A coherence parameter characterizing generative compressed sensing with Fourier measurements
In Bora et al. (2017), a mathematical framework was developed for compressed sensing guarantees in the setting where the measurement matrix is Gaussian and the signal structure is the range of a generative neural network (GNN).
Improving the Deferred Acceptance with Minimal Compromise
When the objective is to improve students' welfare over the SOSM, this characterization implies an important insight into the frontier of the main axioms in school choice.
Sub-Gaussian Matrices on Sets: Optimal Tail Dependence and Applications
In many applications, e. g., compressed sensing, this norm may be large, or even growing with dimension, and thus it is important to characterize this dependence.
Near-optimal sample complexity for convex tensor completion
In this paper, we show that by using an atomic-norm whose atoms are rank-$1$ sign tensors, one can obtain a sample complexity of $O(dN)$.
