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Found 3 papers, 1 papers with code
Certifiable Robustness for Naive Bayes Classifiers
We present (i) a linear time algorithm in the number of entries in the dataset that decides whether a test point is certifiably robust for NBC, (ii) an algorithm that counts for each label, the number of cleaned datasets on which the NBC can be trained to predict that label, and (iii) an efficient optimal algorithm that poisons a clean dataset by inserting the minimum number of missing values such that a test point is not certifiably robust for NBC.
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.
