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Mutual Information Estimation via Normalizing Flows
We propose a novel approach to the problem of mutual information (MI) estimation via introducing normalizing flows-based estimator.
Information Bottleneck Analysis of Deep Neural Networks via Lossy Compression
Our approach leverages the stochastic NN method proposed by Goldfeld et al. (2019) and incorporates a compression step to overcome the obstacles associated with high dimensionality.
Federated Privacy-preserving Collaborative Filtering for On-Device Next App Prediction
Since the data about user experience are distributed among devices, the federated learning setup is used to train the proposed sequential matrix factorization model.
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