Rate-constrained minimum entropy coupling enables cross-domain lossy compression with classification preservation, providing closed-form solutions for Bernoulli sources and neural implementations for MNIST and SVHN tasks.
Minimum-entropy couplings and their applications
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Rényi entropy is subadditive on the majorization lattice for every α ∈ [0,∞] and supermodular for α ∈ {0} ∪ [1,∞]; Tsallis entropy is subadditive and supermodular for all α ∈ [0,∞).
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Cross-Domain Lossy Compression via Constrained Minimum Entropy Coupling
Rate-constrained minimum entropy coupling enables cross-domain lossy compression with classification preservation, providing closed-form solutions for Bernoulli sources and neural implementations for MNIST and SVHN tasks.
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Geometry of R\'enyi Entropy on the Majorization Lattice
Rényi entropy is subadditive on the majorization lattice for every α ∈ [0,∞] and supermodular for α ∈ {0} ∪ [1,∞]; Tsallis entropy is subadditive and supermodular for all α ∈ [0,∞).