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rademacher complexity

109 papers

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RC

Co-occurring keywords

generalization bound (652) kernel methods (1097) neural network (6616) learning theory (519) empirical risk minimization (352) sample complexity (1169) multi-class classification (280) risk bound (71) covering number (34) online learning (1777)

Papers

DS-Compatible Log-Linear Reliability with KL-Prox EM: Monotone Ascent, Identifiability, and Generalization ALT 2026
Rademacher Complexity for Distributionally Robust Learning AAAI 2026
Enhanced Feature Learning via Regularisation: Integrating Neural Networks and Kernel Methods JMLR 2025
Trajectory-Dependent Generalization Bounds for Pairwise Learning with φ-mixing Samples IJCAI 2025
Generalization Error Bounds for Two-stage Recommender Systems with Tree Structure NIPS 2024
To Pool or Not To Pool: Analyzing the Regularizing Effects of Group-Fair Training on Shared Models AISTATS 2024
Rademacher complexity of neural ODEs via Chen-Fliess series L4DC 2024
Neural Networks with Sparse Activation Induced by Large Bias: Tighter Analysis with Bias-Generalized NTK JMLR 2024
Boosting Adversarial Training via Fisher-Rao Norm-based Regularization CVPR 2024
Convolutional Spectral Kernel Learning with Generalization Guarantees (Abstract Reprint) AAAI 2024
Bridging the Gap: Rademacher Complexity in Robust and Standard Generalization COLT 2024
Sequence Length Independent Norm-Based Generalization Bounds for Transformers AISTATS 2024
On the Intrinsic Structures of Spiking Neural Networks JMLR 2024
The sample complexity of ERMs in stochastic convex optimization AISTATS 2024
Towards Empirical Process Theory for Vector-Valued Functions: Metric Entropy of Smooth Function Classes ALT 2023
On Learning Latent Models with Multi-Instance Weak Supervision NIPS 2023
Generalization Guarantees via Algorithm-dependent Rademacher Complexity COLT 2023
Learning with Explanation Constraints NIPS 2023
Generalization Bounds for Adversarial Contrastive Learning JMLR 2023
Generalization Analysis for Contrastive Representation Learning ICML 2023
Tight and fast generalization error bound of graph embedding in metric space ICML 2023
Deep learning with kernels through RKHM and the Perron-Frobenius operator NIPS 2023
Tighter Information-Theoretic Generalization Bounds from Supersamples ICML 2023
Nearly-tight Bounds for Deep Kernel Learning ICML 2023
Exploring the Relationship Between Architectural Design and Adversarially Robust Generalization CVPR 2023