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Found 5 papers, 3 papers with code
Differentially Private Decentralized Deep Learning with Consensus Algorithms
Furthermore, we show that it is possible to learn a model achieving high accuracies, within 3% of DP-SGD on MNIST under (1, 10^-5)-differential privacy and within 6% of DP-SGD on CIFAR-100 under (10, 10^-5)-differential privacy, without ever sharing raw data with other agents.
Multispectral Contrastive Learning with Viewmaker Networks
Contrastive learning methods have been applied to a range of domains and modalities by training models to identify similar "views" of data points.
Temperature as Uncertainty in Contrastive Learning
In this paper, we propose a simple way to generate uncertainty scores for many contrastive methods by re-purposing temperature, a mysterious hyperparameter used for scaling.
Reading Between the Demographic Lines: Resolving Sources of Bias in Toxicity Classifiers
The censorship of toxic comments is often left to the judgment of imperfect models.
Keep Your AI-es on the Road: Tackling Distracted Driver Detection with Convolutional Neural Networks and Targeted Data Augmentation
According to the World Health Organization, distracted driving is one of the leading cause of motor accidents and deaths in the world.
