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Found 3 papers, 1 papers with code
Naive Bayes Classifiers over Missing Data: Decision and Poisoning
We study the certifiable robustness of ML classifiers on dirty datasets that could contain missing values.
A Real-time Contribution Measurement Method for Participants in Federated Learning
However, there is a lack of a sufficiently reasonable contribution measurement mechanism to distribute the reward for each agent.
Scalable inference of topic evolution via models for latent geometric structures
We develop new models and algorithms for learning the temporal dynamics of the topic polytopes and related geometric objects that arise in topic model based inference.
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