The Dual Information Bottleneck

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We present a new framework, the Dual Information Bottleneck (dualIB), which resolves some of the known drawbacks of the Information Bottleneck. We provide a theoretical analysis of the dualIB framework and solving for the structure of its solutions. To approach large scale problems, we present a novel variational formulation of the dualIB for Deep Neural Networks. In experiments on several data-sets, we compare it to a variational form of the IB.

Ravid Shwartz-Ziv
Ravid Shwartz-Ziv
Assistant Professor and Faculty Fellow