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Generalization Bounds

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TitleStatusHype
Information-Theoretic Generalization Bounds of Replay-based Continual Learning—0
Tuning without Peeking: Provable Privacy and Generalization Bounds for LLM Post-Training—0
Tight Generalization Error Bounds for Stochastic Gradient Descent in Non-convex Learning—0
Sharp Generalization Bounds for Foundation Models with Asymmetric Randomized Low-Rank Adapters—0
Stability Analysis of Physics-Informed Neural Networks via Variational Coercivity, Perturbation Bounds, and Concentration Estimates—0
Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective—0
Neural Drift Estimation for Ergodic Diffusions: Non-parametric Analysis and Numerical Exploration—0
Epistemic Errors of Imperfect Multitask Learners When Distributions Shift—0
Learning Where to Learn: Training Distribution Selection for Provable OOD PerformanceCode0
Operator Learning for Schrödinger Equation: Unitarity, Error Bounds, and Time GeneralizationCode0
Generalization Through Growth: Hidden Dynamics Controls Depth Dependence—0
Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes—0
Graph Representational Learning: When Does More Expressivity Hurt Generalization?Code0
Generalization Bounds for Quantum Learning via Rényi Divergences—0
Efficient End-to-End Learning for Decision-Making: A Meta-Optimization Approach—0
Generalization Bounds and Stopping Rules for Learning with Self-Selected Data—0
Model Steering: Learning with a Reference Model Improves Generalization Bounds and Scaling LawsCode0
Generalization Analysis for Contrastive Representation Learning under Non-IID Settings—0
Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior—0
Achieving Distributive Justice in Federated Learning via Uncertainty QuantificationCode0
Compute-Optimal LLMs Provably Generalize Better With Scale—0
Generalization Bounds in Hybrid Quantum-Classical Machine Learning Models—0
Architecture independent generalization bounds for overparametrized deep ReLU networks—0
Improving Equivariant Networks with Probabilistic Symmetry Breaking—0
Non-vacuous Generalization Bounds for Deep Neural Networks without any modification to the trained models—0
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