Tag archive
Analyzing how Bernoulli Boolean types propagate through logic circuits, with correctness probabilities for noisy AND gates and interval arithmetic for composed circuits.
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.
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.
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.
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.
TL;DR: HyperLogLog (HLL) is a probabilistic data structure that estimates unique counts by analyzing...