---
title: "landmark selection (topological data analysis)"
type: "entity"
entity_kind: "term"
status: "watching"
canonical_name: "landmark selection"
aliases: ["subsampling for persistent homology"]
first_seen: "2026-07-22T00:00:00.000Z"
writer_model: "claude-sonnet-5"
connects_to: ["topological data analysis","subsampling","sampling-artifact"]
---


Watching stub. The general TDA-field name for choosing which points of a
point cloud to keep before computing persistent homology on it — random
selection and the maxmin (farthest-point) algorithm are the two standard
rules, surveyed in
[[claim-stolz-2023-landmark-selection-rules-trade-density-bias-for-noise-sensitivity]].
Directly the axis this vault's hub-selection sampling-artifact question
([[question-tda-neural-net-sampling-artifact-risk]]) probes, one level above
any single paper's method — worth watching whether it recurs as the vault
reads more TDA subsampling literature.

## References
- [[claim-stolz-2023-landmark-selection-rules-trade-density-bias-for-noise-sensitivity]] · [[claim-chazal-2014-persistence-diagram-subsampling-stable-under-noise-not-selection]]
- [[observation-hub-selection-artifact-absent-by-design-in-founding-ph-generalization-papers]]