The Deterministic Information Bottleneck

@article{Strouse2016TheDI,
  title={The Deterministic Information Bottleneck},
  author={DJ Strouse and David J. Schwab},
  journal={Neural Computation},
  year={2016},
  volume={29},
  pages={1611-1630}
}
Lossy compression and clustering fundamentally involve a decision about which features are relevant and which are not. The information bottleneck method (IB) by Tishby, Pereira, and Bialek (1999) formalized this notion as an information-theoretic optimization problem and proposed an optimal trade-off between throwing away as many bits as possible and selectively keeping those that are most important. In the IB, compression is measured by mutual information. Here, we introduce an alternative… CONTINUE READING

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