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Tag: learner

  • Robust X-Learner: Breaking the Curse of Imbalance and Heavy Tails via Robust Cross-Imputation

    Robust X-Learner: Breaking the Curse of Imbalance and Heavy Tails via Robust Cross-Imputation arXiv:2601.15360v1 Announce Type: new Abstract: Estimating Heterogeneous Treatment Effects (HTE) in industrial applications such as AdTech and healthcare presents a dual challenge: extreme class imbalance and heavy-tailed outcome distributions. While the X-Learner framework effectively addresses imbalance through cross-imputation, we demonstrate that it…

  • Robust estimation of heterogeneous treatment effects in randomized trials leveraging external data

    Robust estimation of heterogeneous treatment effects in randomized trials leveraging external data arXiv:2507.03681v1 Announce Type: new Abstract: Randomized trials are typically designed to detect average treatment effects but often lack the statistical power to uncover effect heterogeneity over patient characteristics, limiting their value for personalized decision-making. To address this, we propose the QR-learner, a model-agnostic…

  • Ensuring superior learning outcomes and data security for authorized learner

    Ensuring superior learning outcomes and data security for authorized learner arXiv:2501.00754v1 Announce Type: new Abstract: The learner’s ability to generate a hypothesis that closely approximates the target function is crucial in machine learning. Achieving this requires sufficient data; however, unauthorized access by an eavesdropping learner can lead to security risks. Thus, it is important to…