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Tag: weighting

  • A General Weighting Theory for Ensemble Learning: Beyond Variance Reduction via Spectral and Geometric Structure

    A General Weighting Theory for Ensemble Learning: Beyond Variance Reduction via Spectral and Geometric Structure arXiv:2512.22286v1 Announce Type: new Abstract: Ensemble learning is traditionally justified as a variance-reduction strategy, explaining its strong performance for unstable predictors such as decision trees. This explanation, however, does not account for ensembles constructed from intrinsically stable estimators-including smoothing splines,…

  • The Interplay of Statistics and Noisy Optimization: Learning Linear Predictors with Random Data Weights

    The Interplay of Statistics and Noisy Optimization: Learning Linear Predictors with Random Data Weights arXiv:2512.10188v1 Announce Type: new Abstract: We analyze gradient descent with randomly weighted data points in a linear regression model, under a generic weighting distribution. This includes various forms of stochastic gradient descent, importance sampling, but also extends to weighting distributions with…

  • Self-adaptive weighting and sampling for physics-informed neural networks

    Self-adaptive weighting and sampling for physics-informed neural networks arXiv:2511.05452v1 Announce Type: new Abstract: Physics-informed deep learning has emerged as a promising framework for solving partial differential equations (PDEs). Nevertheless, training these models on complex problems remains challenging, often leading to limited accuracy and efficiency. In this work, we introduce a hybrid adaptive sampling and weighting…

  • Decorrelated feature importance from local sample weighting

    Decorrelated feature importance from local sample weighting arXiv:2508.06337v1 Announce Type: new Abstract: Feature importance (FI) statistics provide a prominent and valuable method of insight into the decision process of machine learning (ML) models, but their effectiveness has well-known limitations when correlation is present among the features in the training data. In this case, the FI…