A support-aware DSS integrates replay, OPE, lower-bound ranking, multi-sided guardrails, out-of-time validation, and interference-aware design to output launch-readiness classifications rather than single performance estimates, applied to RTB logs where a margin-gated floor policy is selected for va
Bid landscape forecasting in online ad exchange marketplace
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Introduces a framework that converts sparse incrementality experiment lifts into daily attribution corrections under structural constraints, reducing calibration error and measured cannibalization rate by ~15pp in TikTok deployments.
citing papers explorer
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Decision Support for Marketplace Policies under Incomplete Evidence: From Replay to Launch Readiness
A support-aware DSS integrates replay, OPE, lower-bound ranking, multi-sided guardrails, out-of-time validation, and interference-aware design to output launch-readiness classifications rather than single performance estimates, applied to RTB logs where a margin-gated floor policy is selected for va
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Attributed, But Not Incremental: Cannibalization-Corrected Attribution for Large-Scale Advertising
Introduces a framework that converts sparse incrementality experiment lifts into daily attribution corrections under structural constraints, reducing calibration error and measured cannibalization rate by ~15pp in TikTok deployments.