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lipschitz loss

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regret bound (2) adversarial contrastive learning (1) negative sample (1) interpolation learning (1) differentially private (1) radamacher complexity (1) second order gradient adaptivity (1) comparator norm adaptivity (1) discretization argument (1) online nonparametric learning (1)

Papers

Bounding the Excess Risk for Linear Models Trained on Marginal-Preserving, Differentially-Private, Synthetic Data ICML 2024 Fully Unconstrained Online Learning NeurIPS 2024 Improving Adaptive Online Learning Using Refined Discretization ALT 2024 Towards Sharper Generalization Bounds for Adversarial Contrastive Learning IJCAI 2024 Uniform Convergence with Square-Root Lipschitz Loss NeurIPS 2023 Robust high dimensional learning for Lipschitz and convex losses JMLR 2020 Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning COLT 2017