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DataFunTalk
DataFunTalk
Jan 7, 2023 · Artificial Intelligence

How to Better Leverage Data in Causal Inference

This presentation introduces two recent works from Ant Group that improve causal inference by explicitly using historical control data to reduce selection bias and by fusing heterogeneous multi‑source data, describing the GBCT and WMDL methods, their theoretical foundations, experimental results, and practical applications in finance.

bias correctioncausal inferencedata fusion
0 likes · 18 min read
How to Better Leverage Data in Causal Inference
Alimama Tech
Alimama Tech
May 18, 2022 · Artificial Intelligence

Multiple Boosting Calibration Trees (MBCT): Feature‑Aware Binning for Uncertainty Calibration

The paper introduces Multiple Boosting Calibration Trees, a feature‑aware binning ensemble that uses a new multi‑view calibration error metric and boosting to learn personalized, non‑monotonic calibrations for CTR prediction, achieving lower calibration error and higher click‑through rates and revenue than existing methods in both offline and online tests.

MVCEadvertisingfeature-aware binning
0 likes · 18 min read
Multiple Boosting Calibration Trees (MBCT): Feature‑Aware Binning for Uncertainty Calibration