A Moment of Perfect Clarity I: The Parallel Census Technique
Christian Glasser, Lane A. Hemaspaandra

TL;DR
This paper explores the parallel census technique, an elegant method for studying computational objects with polynomially bounded census functions, and discusses its historical development and applications in complexity theory.
Contribution
It provides a comprehensive overview of the parallel census technique and its role in complexity class collapses related to NP-hard sets and reductions.
Findings
The parallel census technique is effective in analyzing polynomially bounded census functions.
Historical and recent applications of the technique are discussed, including complexity class implications.
Connections to NP-hard sets and reductions are explored.
Abstract
We discuss the history and uses of the parallel census technique---an elegant tool in the study of certain computational objects having polynomially bounded census functions. A sequel will discuss advances (including Cai, Naik, and Sivakumar [CNS95] and Glasser [Gla00]), some related to the parallel census technique and some due to other approaches, in the complexity-class collapses that follow if NP has sparse hard sets under reductions weaker than (full) truth-table reductions.
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Taxonomy
TopicsMachine Learning and Algorithms · Complexity and Algorithms in Graphs · Bayesian Modeling and Causal Inference
