The Bernoulli Model
Random approximate computation: the Bernoulli model, its papers, and the monograph that unifies them. Bloom filters are the special case; this is the general theory.
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Random approximate computation: the Bernoulli model, its papers, and the monograph that unifies them. Bloom filters are the special case; this is the general theory.
Entropy maps use prefix-free hash codes to approximate functions without storing the domain, achieving information-theoretic space bounds with controllable error.
Entropy maps use prefix-free hash codes to approximate functions without storing the domain, achieving information-theoretic space bounds with controllable error.
A Boolean algebra framework over trapdoors for cryptographic operations. Introduces a homomorphism from powerset Boolean algebra to n-bit strings via cryptographic hash functions, enabling secure computations with one-way properties.
Analyzing how Bernoulli Boolean types propagate through logic circuits, with correctness probabilities for noisy AND gates and interval arithmetic for composed circuits.
The Bernoulli Model is a framework for reasoning about probabilistic data structures by treating noisy outputs as Bernoulli-distributed approximations of latent values, from Booleans to set-indicator functions.
The Bernoulli Model is a framework for reasoning about probabilistic data structures by treating noisy outputs as Bernoulli-distributed approximations of latent values, from Booleans to set-indicator functions.
Bloom filters trade perfect recall for extraordinary space efficiency. How they work and why they matter.