Sample Size

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3 papers in the last 28 days · 0.1% of indexed attention

Twelve weeks of publication activity for this topic as it is defined today.

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Period ending 2026-09-14

3 new papers

A weekly snapshot of new work published in Sample Size.

31 papers

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  1. A Statistical Approach to Estimating Sample Size of Machine Learning Models

    Sep 10, 2026Dat Phan-Trong, Sunil Gupta, Svetha VenkateshSample SizeMachine Learning

  2. A Kernel-Based Modular Discriminant Analysis Framework for Small-Sample Learning

    Sep 9, 2026Lingxiao Qu, Yan PeiPrincipal Component AnalysisSample Size

  3. Length Generalization for Transformers via Compression

    Sep 8, 2026Georg Zetzsche, Hongjian Jiang, Andy Yang +4Transformer VariantGeneralization Bounds

  4. Small-Scale Experiments: Are We There Yet?

    Aug 12, 2026Nicholas Lourie, Kyunghyun Cho, Karen Ullrich +1Scaling LawsHyperparameter

  5. A Systematic Sample Size Analysis of ML-Based Path Loss Prediction for LPWAN

    Aug 11, 2026Robert Bitterling, Christian Nettersheim, Jörn Hees +1Wireless NetworksSample Size

  6. Target-Weighted Neyman Allocation: Experimental Design for Heterogeneous Treatment Effects under Population Shift

    Aug 6, 2026Hoang Dang, Luan Pham, Minh NguyenHeterogeneous Treatment EffectsBayesian Experimental Design

  7. Demographically-Conditioned Synthetic Medical Images for Bias Mitigation and Bias Detection in Disease Classifiers

    Jul 16, 2026Mahmoud Ibrahim, Bart Elen, Chang Sun +2Medical Image GenerationFairness Audits

  8. Data-Efficient Deep Learning: Empirical Guidelines for Training Set Size Estimation in Inertial Sensor Classification

    Jul 10, 2026Ofir Kruzel, Itzik KlienInertial Measurement UnitsSample Size

  9. Heat-Kernel Entropy Profiles and Geometric Effective Sample Size for Weighted Measures on Manifolds

    Jul 7, 2026Kisung YouWasserstein DistanceSample Size

  10. Applicability of memorization indicators for early spotting of overfitting while recalibrating sEMG-decoders on low sample sizes

    Jun 26, 2026Stephan J. Lehmler, Tobias Glasmachers, Ioannis IossifidisSurface ElectromyographyMemorization

  11. Estimating Uncertainty in Classifier Performance with Applications to Large Language Models and Nested Data

    Jun 24, 2026Kylie AnglinConfidence IntervalsMultiplier Bootstrap

  12. When Do Local Score Models Extrapolate Across Size? A Diagnostic Theory and Benchmark

    Jun 8, 2026Wenjie XiScore-Based Diffusion ModelExtrapolation

  13. The price of multi-group transductive learning

    Jun 3, 2026Noah Bergam, Samuel Deng, Daniel HsuTransductive Active LabelingMulticlass Classification

  14. Finding Needles in the Haystack: Transductive Active Labeling in Ecology

    Jun 2, 2026Rupa Kurinchi-Vendhan, Sara BeeryTransductive Active LabelingActive Learning

  15. Sample-Size Scaling of the African Languages NLI Evaluation

    Jun 2, 2026Anuj Tiwari, Oluwapelumi Ogunremu, Terry Oko-odion +2Multilingual Language ModelsLegal Natural Language Processing Benchmarks

  16. Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing

    Jun 1, 2026Arda Fazla, Abolfazl HashemiSelection BiasEmpirical Risk Minimization

  17. Repetition Mismatch: Why Data Mixture Experiments Don't Scale and How to Fix Them

    May 29, 2026Kevin Zhou, Lisa Alazraki, Kris Cao +1RepetitionMixtures

  18. The Privacy Price of Tail-Risk Learning: Effective Tail Sample Size in Differentially Private CVaR Optimization

    May 15, 2026El Mustapha MansouriConditional-Value-At-RiskHeavy-Tailed Noise

  19. Understanding Sample Efficiency in Predictive Coding

    May 12, 2026Gaspard Oliviers, Elene Lominadze, Rafal BogaczPredictive CodingSingular Learning Theory

  20. Federated Language Models Under Bandwidth Budgets: Distillation Rates and Conformal Coverage

    May 11, 2026Prasanjit Dubey, Xiaoming HuoBandwidth ExtensionDistributional Learning

  21. How Much is Brain Data Worth for Machine Learning?

    May 10, 2026Lane Lewis, Zhixin Wang, David Schwab +1Machine LearningSequential Learning

  22. Prediction Bottlenecks Don't Discover Causal Structure (But Here's What They Actually Do)

    May 9, 2026Ankit Hemant Lade, Sai Krishna Jasti, Indar Kumar +1Structural Causal ModelCausal Structure and Reasoning

  23. Survey-aware Machine Learning: A Guideline for Valid Population Health Inference based on Scoping Review

    May 9, 2026YongKyung Oh, Henry W. Zheng, Jeffrey Feng +1SurveyMachine Learning

  24. Intrinsic effective sample size for manifold-valued Markov chain Monte Carlo via kernel discrepancy

    May 5, 2026Kisung YouMonte Carlo SamplingSample Size

  25. RuC: HDL-Agnostic Rule Completion Benchmark Generation

    Apr 30, 2026Arnau Ayguadé Domingo, Miquel Alberti-Binimelis, Cristian Gutierrez-Gomez +5Hardware Description LanguagesCode Completion

  26. Unstable Rankings in Bayesian Deep Learning Evaluation

    Apr 25, 2026Qishi Zhan, Minxuan Hu, Guansu Wang +2Bayesian Neural NetworksSample Size

  27. Fast estimation of Gaussian mixture components via centering and singular value thresholding

    Apr 21, 2026Huan QingGaussian Mixture ModelsHigh-Dimensional

  28. How Much Data is Enough? The Zeta Law of Discoverability in Biomedical Data, featuring the enigmatic Riemann zeta function

    Apr 19, 2026Paul M. ThompsonScaling LawsBiomedical

  29. Covariance-Based Structural Equation Modeling in Small-Sample Settings with p>n

    Apr 18, 2026Hiroki Hasegawa, Aoba Tamura, Yukihiko OkadaStructural Equation ModelingCovariance Estimation

  30. Maximum Mean Discrepancy with Unequal Sample Sizes via Generalized U-Statistics

    Dec 16, 2025Aaron Wei, Milad Jalali, Danica J. SutherlandMaximum Mean DiscrepancyTwo-Sample Testing

  31. Multiple Testing of Linear Forms for Noisy Matrix Completion

    Dec 1, 2023Wanteng Ma, Lilun Du, Dong Xia +1Tensor CompletionFalse Discovery Rate