Maximum Entropy Relaxation of Multi-Way Cardinality Constraints for Synthetic Population Generation
Generating synthetic populations from aggregate statistics is a core component of microsimulation, agent-based modeling, policy analysis, and privacy-preserving data release. Beyond classical census marginals, many applications require matching heterogeneous unary, binary, and ternary constraints derived from surveys, expert knowledge, or automatically extracted descriptions. Constructing populations that satisfy such multi-way constraints simultaneously poses a significant computational challenge. We consider populations where each individual is described by categorical attributes and the target is a collection of global frequency constraints over attribute combinations. Exact formulatio...
| Authors | François Pachet, Jean-Daniel Zucker |
|---|---|
| Primary category | cs.AI |
| Published | 23 March 2026 |
| Last updated at source | 11 April 2026 |
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