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Generalization Bounds

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TitleStatusHype
The Ideal Continual Learner: An Agent That Never ForgetsCode4
Effective Sample Size, Dimensionality, and Generalization in Covariate Shift AdaptationCode1
How Does Information Bottleneck Help Deep Learning?Code1
Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive LossCode1
PACOH: Bayes-Optimal Meta-Learning with PAC-GuaranteesCode1
Deep Learning and the Information Bottleneck PrincipleCode1
Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-TuningCode1
Non-IID Transfer Learning on GraphsCode1
PAC-Bayes Compression Bounds So Tight That They Can Explain GeneralizationCode1
Principles and Algorithms for Forecasting Groups of Time Series: Locality and GlobalityCode1
The Complexity Dynamics of GrokkingCode1
PerAda: Parameter-Efficient Federated Learning Personalization with Generalization GuaranteesCode1
PAC-Bayesian Generalization Bounds for Knowledge Graph Representation LearningCode1
On PAC-Bayesian Bounds for Random ForestsCode1
Non-Vacuous Generalization Bounds for Large Language ModelsCode1
In Search of Robust Measures of GeneralizationCode1
Measuring Generalization with Optimal TransportCode1
NICO++: Towards Better Benchmarking for Domain GeneralizationCode1
SWAD: Domain Generalization by Seeking Flat MinimaCode1
Optimal Auctions through Deep Learning: Advances in Differentiable EconomicsCode1
PAC Confidence Sets for Deep Neural Networks via Calibrated PredictionCode1
Personalized Federated Learning through Local MemorizationCode1
Energy-guided Entropic Neural Optimal TransportCode1
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware MixupCode1
Estimating individual treatment effect: generalization bounds and algorithmsCode1
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event DataCode1
Evaluation of Complexity Measures for Deep Learning Generalization in Medical Image AnalysisCode1
Fast Interpretable Greedy-Tree SumsCode1
Do Generated Data Always Help Contrastive Learning?Code1
Out-of-distributional risk bounds for neural operators with applications to the Helmholtz equationCode1
Generalization Guarantees for Imitation LearningCode1
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph DiffusionCode1
Improving Generalization by Controlling Label-Noise Information in Neural Network WeightsCode1
Bridging Theory and Algorithm for Domain AdaptationCode1
AdapterGNN: Parameter-Efficient Fine-Tuning Improves Generalization in GNNsCode1
Learning to Warm-Start Fixed-Point Optimization AlgorithmsCode1
Minimax Classification with 0-1 Loss and Performance GuaranteesCode1
Learning Robust State Abstractions for Hidden-Parameter Block MDPsCode1
Debiased Contrastive LearningCode1
Relative Flatness and GeneralizationCode0
Generalization Bounds for Sparse Random Feature ExpansionsCode0
Exploring the Algorithm-Dependent Generalization of AUPRC Optimization with List StabilityCode0
Generalization Bound and New Algorithm for Clean-Label Backdoor AttackCode0
Escaping the Curse of Dimensionality in Similarity Learning: Efficient Frank-Wolfe Algorithm and Generalization BoundsCode0
Enhancing In-Context Learning Performance with just SVD-Based Weight Pruning: A Theoretical PerspectiveCode0
A PAC-Bayesian Framework for Optimal Control with Stability GuaranteesCode0
Algorithm-Dependent Bounds for Representation Learning of Multi-Source Domain AdaptationCode0
Graph Representational Learning: When Does More Expressivity Hurt Generalization?Code0
A PAC-Bayesian Analysis of Randomized Learning with Application to Stochastic Gradient DescentCode0
An Algorithmic Framework for Fairness ElicitationCode0
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