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Generalization Bounds

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TitleStatusHype
The Ideal Continual Learner: An Agent That Never ForgetsCode4
The Complexity Dynamics of GrokkingCode1
PAC-Bayesian Generalization Bounds for Knowledge Graph Representation LearningCode1
Do Generated Data Always Help Contrastive Learning?Code1
Non-Vacuous Generalization Bounds for Large Language ModelsCode1
Learning to Warm-Start Fixed-Point Optimization AlgorithmsCode1
How Does Information Bottleneck Help Deep Learning?Code1
AdapterGNN: Parameter-Efficient Fine-Tuning Improves Generalization in GNNsCode1
Energy-guided Entropic Neural Optimal TransportCode1
PerAda: Parameter-Efficient Federated Learning Personalization with Generalization GuaranteesCode1
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph DiffusionCode1
Out-of-distributional risk bounds for neural operators with applications to the Helmholtz equationCode1
Non-IID Transfer Learning on GraphsCode1
PAC-Bayes Compression Bounds So Tight That They Can Explain GeneralizationCode1
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware MixupCode1
NICO++: Towards Better Benchmarking for Domain GeneralizationCode1
Fast Interpretable Greedy-Tree SumsCode1
Personalized Federated Learning through Local MemorizationCode1
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event DataCode1
Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive LossCode1
Measuring Generalization with Optimal TransportCode1
Evaluation of Complexity Measures for Deep Learning Generalization in Medical Image AnalysisCode1
SWAD: Domain Generalization by Seeking Flat MinimaCode1
Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-TuningCode1
In Search of Robust Measures of GeneralizationCode1
Minimax Classification with 0-1 Loss and Performance GuaranteesCode1
Effective Sample Size, Dimensionality, and Generalization in Covariate Shift AdaptationCode1
Generalization Guarantees for Imitation LearningCode1
Principles and Algorithms for Forecasting Groups of Time Series: Locality and GlobalityCode1
Learning Robust State Abstractions for Hidden-Parameter Block MDPsCode1
Debiased Contrastive LearningCode1
Improving Generalization by Controlling Label-Noise Information in Neural Network WeightsCode1
PACOH: Bayes-Optimal Meta-Learning with PAC-GuaranteesCode1
PAC Confidence Sets for Deep Neural Networks via Calibrated PredictionCode1
Bridging Theory and Algorithm for Domain AdaptationCode1
On PAC-Bayesian Bounds for Random ForestsCode1
Optimal Auctions through Deep Learning: Advances in Differentiable EconomicsCode1
Estimating individual treatment effect: generalization bounds and algorithmsCode1
Deep Learning and the Information Bottleneck PrincipleCode1
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
Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes—0
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