pith:XPMPOXGZ
Optimal Recourse Summaries via Bi-Objective Decision Tree Learning
SOGAR finds the complete Pareto front of recourse summaries by learning bi-objective decision trees that balance effectiveness against cost.
arxiv:2605.07598 v2 · 2026-05-08 · cs.LG
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Claims
SOGAR enables post-hoc selection of the desired trade-off without retraining. Using shallow axis-parallel decision trees and sparse leaf actions, SOGAR produces stable, low-cost, and effective recourse summaries that outperform existing approaches across effectiveness and cost metrics.
That shallow axis-parallel decision trees combined with sparse leaf actions are sufficient to produce stable, globally effective recourse summaries without losing critical population structure or requiring more expressive models.
SOGAR learns Pareto-optimal recourse summaries by solving a bi-objective decision tree problem, yielding stable low-cost effective group actions that outperform prior methods on effectiveness and cost.
Formal links
Receipt and verification
| First computed | 2026-05-22T01:04:05.286712Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
bbd8f75cd94e7134d62087d55dc7357dd007b0819d29a41ead0cc815ec31cd54
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/XPMPOXGZJZYTJVRAQ7KV3RZVPX \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: bbd8f75cd94e7134d62087d55dc7357dd007b0819d29a41ead0cc815ec31cd54
Canonical record JSON
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