sample compression

Bound to Disagree: Generalization Bounds via Certifiable Surrogates UAI 2026 Boosting, Voting Classifiers and Randomized Sample Compression Schemes ALT 2025 Sample Compression Unleashed: New Generalization Bounds for Real Valued Losses AISTATS 2025 Agnostic Sample Compression Schemes for Regression ICML 2024 Dual VC Dimension Obstructs Sample Compression by Embeddings COLT 2024 List Sample Compression and Uniform Convergence COLT 2024 Multiclass Learnability Does Not Imply Sample Compression ALT 2024 Sample-Efficient Private Learning of Mixtures of Gaussians NeurIPS 2024 The Star Number and Eluder Dimension: Elementary Observations About the Dimensions of Disagreement COLT 2024 Adversarially Robust PAC Learnability of Real-Valued Functions ICML 2023 Compress Then Test: Powerful Kernel Testing in Near-linear Time AISTATS 2023 Private Distribution Learning with Public Data: The View from Sample Compression NeurIPS 2023 Sample Complexity Bounds for Learning High-dimensional Simplices in Noisy Regimes ICML 2023 Realizable Learning is All You Need COLT 2022 Unlabelled Sample Compression Schemes for Intersection-Closed Classes and Extremal Classes NeurIPS 2022 VC dimension of partially quantized neural networks in the overparametrized regime ICLR 2022 Bounded Memory Active Learning through Enriched Queries COLT 2021 Stable Sample Compression Schemes: New Applications and an Optimal SVM Margin Bound ALT 2021 A Sharp Lower Bound for Agnostic Learning with Sample Compression Schemes ALT 2019 Sample Compression for Real-Valued Learners ALT 2019 Active Nearest-Neighbor Learning in Metric Spaces JMLR 2018 Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes NeurIPS 2018 Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions NeurIPS 2017 Nearly optimal classification for semimetrics JMLR 2017 Optimal learning via local entropies and sample compression COLT 2017