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Generalization Bounds

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TitleStatusHype
Teacher Guided Training: An Efficient Framework for Knowledge Transfer—0
On Rademacher Complexity-based Generalization Bounds for Deep Learning—0
Integral Probability Metrics PAC-Bayes BoundsCode0
On Leave-One-Out Conditional Mutual Information For Generalization—0
Robustness Implies Generalization via Data-Dependent Generalization Bounds—0
On how to avoid exacerbating spurious correlations when models are overparameterized—0
Cold Posteriors through PAC-Bayes—0
Data Augmentation vs. Equivariant Networks: A Theory of Generalization on Dynamics Forecasting—0
On the Role of Generalization in Transferability of Adversarial Examples—0
Provable Generalization of Overparameterized Meta-learning Trained with SGD—0
Generalization Bounds for Data-Driven Numerical Linear Algebra—0
Max-Margin Works while Large Margin Fails: Generalization without Uniform Convergence—0
Memory Classifiers: Two-stage Classification for Robustness in Machine Learning—0
What is a Good Metric to Study Generalization of Minimax Learners?—0
Learning Non-Vacuous Generalization Bounds from OptimizationCode0
Boosting the Confidence of Generalization for L_2-Stable Randomized Learning Algorithms—0
Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein DistancesCode0
Reconsidering Learning Objectives in Unbiased Recommendation with Unobserved Confounders—0
Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization GuaranteesCode0
Rate-Distortion Theoretic Bounds on Generalization Error for Distributed LearningCode0
Dimension Independent Generalization of DP-SGD for Overparameterized Smooth Convex Optimization—0
Optimal Weak to Strong Learning—0
A Communication-efficient Algorithm with Linear Convergence for Federated Minimax Learning—0
VC Theoretical Explanation of Double Descent—0
Generalization bounds and algorithms for estimating conditional average treatment effect of dosage—0
Generalization Bounds of Nonconvex-(Strongly)-Concave Stochastic Minimax Optimization—0
Generalization Bounds for Gradient Methods via Discrete and Continuous Prior—0
Learning Distributions by Generative Adversarial Networks: Approximation and Generalization—0
Uniform Generalization Bound on Time and Inverse Temperature for Gradient Descent Algorithm and its Application to Analysis of Simulated Annealing—0
SepIt: Approaching a Single Channel Speech Separation Bound—0
Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient DescentCode0
Towards Size-Independent Generalization Bounds for Deep Operator NetsCode0
Generalization Bounds on Multi-Kernel Learning with Mixed Datasets—0
Formal limitations of sample-wise information-theoretic generalization bounds—0
StableDR: Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random—0
Power of Quantum Generative Learning—0
Learnability of Competitive Threshold ModelsCode0
Out-of-distribution generalization for learning quantum dynamics—0
Dynamical simulation via quantum machine learning with provable generalization—0
NICO++: Towards Better Benchmarking for Domain GeneralizationCode1
Higher-Order Generalization Bounds: Learning Deep Probabilistic Programs via PAC-Bayes Objectives—0
Generalization bounds for learning under graph-dependence: A survey—0
Generalization Through The Lens Of Leave-One-Out ErrorCode0
Rate-Distortion Theoretic Generalization Bounds for Stochastic Learning Algorithms—0
Stability vs Implicit Bias of Gradient Methods on Separable Data and Beyond—0
Towards Unsupervised Domain Adaptation via Domain-Transformer—0
Sample Efficiency of Data Augmentation Consistency Regularization—0
From Optimization Dynamics to Generalization Bounds via Łojasiewicz Gradient Inequality—0
Convex Surrogate Loss Functions for Contextual Pricing with Transaction Data—0
Black-Box Generalization: Stability of Zeroth-Order Learning—0
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