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On the Information Bottleneck for Stable Variables
arXiv math.IT0 views
arXiv:2610.08007v1 Announce Type: new Abstract: We consider a generalization of the Gaussian information bottleneck problem to jointly stable variables $X$ and $Y$. Specifically, for $X = Y + A$, where $A$ is stable and independent of $Y$, we find optimal stochastic linear encoders of the form $T = kX + N$, $N$ being stable and independent of $X$. We characterize the linear stable information bottleneck in closed-form and its critical value. Furthermore, we show that, except for the Gaussian case, such stochastic linear encoders are strictly suboptimal, however asymptotically optimal at large compression rate. Our linear solution recovers the Gaussian information bottleneck for jointly Gaussian variables.
Source:https://arxiv.org/abs/2610.08007PreviousSparse Kernel Mechanisms for Locally Differentially Private Discrete ChannelsNextGraph-Theoretic Bounds for Non-Linear Function Computation Broadcast
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