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Found 3 papers, 3 papers with code
Causal Strategic Learning with Competitive Selection
We study the problem of agent selection in causal strategic learning under multiple decision makers and address two key challenges that come with it.
Preventing Clean Label Poisoning using Gaussian Mixture Loss
Since 2014 when Szegedy et al. showed that carefully designed perturbations of the input can lead Deep Neural Networks (DNNs) to wrongly classify its label, there has been an ongoing research to make DNNs more robust to such malicious perturbations.
Improving Super-Resolution Methods via Incremental Residual Learning
Recently, Convolutional Neural Networks (CNNs) have shown promising performance in super-resolution (SR).
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