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Generalization Bounds

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TitleStatusHype
The Ideal Continual Learner: An Agent That Never ForgetsCode4
In Search of Robust Measures of GeneralizationCode1
Debiased Contrastive LearningCode1
PAC Confidence Sets for Deep Neural Networks via Calibrated PredictionCode1
Personalized Federated Learning through Local MemorizationCode1
Learning to Warm-Start Fixed-Point Optimization AlgorithmsCode1
Energy-guided Entropic Neural Optimal TransportCode1
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph DiffusionCode1
Learning Robust State Abstractions for Hidden-Parameter Block MDPsCode1
PAC-Bayesian Generalization Bounds for Knowledge Graph Representation LearningCode1
The Complexity Dynamics of GrokkingCode1
Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive LossCode1
On PAC-Bayesian Bounds for Random ForestsCode1
Measuring Generalization with Optimal TransportCode1
How Does Information Bottleneck Help Deep Learning?Code1
SWAD: Domain Generalization by Seeking Flat MinimaCode1
Evaluation of Complexity Measures for Deep Learning Generalization in Medical Image AnalysisCode1
Generalization Guarantees for Imitation LearningCode1
Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-TuningCode1
Minimax Classification with 0-1 Loss and Performance GuaranteesCode1
Non-Vacuous Generalization Bounds for Large Language ModelsCode1
PAC-Bayes Compression Bounds So Tight That They Can Explain GeneralizationCode1
Principles and Algorithms for Forecasting Groups of Time Series: Locality and GlobalityCode1
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event DataCode1
PACOH: Bayes-Optimal Meta-Learning with PAC-GuaranteesCode1
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware MixupCode1
PerAda: Parameter-Efficient Federated Learning Personalization with Generalization GuaranteesCode1
Optimal Auctions through Deep Learning: Advances in Differentiable EconomicsCode1
Non-IID Transfer Learning on GraphsCode1
NICO++: Towards Better Benchmarking for Domain GeneralizationCode1
Bridging Theory and Algorithm for Domain AdaptationCode1
Effective Sample Size, Dimensionality, and Generalization in Covariate Shift AdaptationCode1
Deep Learning and the Information Bottleneck PrincipleCode1
Do Generated Data Always Help Contrastive Learning?Code1
AdapterGNN: Parameter-Efficient Fine-Tuning Improves Generalization in GNNsCode1
Estimating individual treatment effect: generalization bounds and algorithmsCode1
Fast Interpretable Greedy-Tree SumsCode1
Out-of-distributional risk bounds for neural operators with applications to the Helmholtz equationCode1
Improving Generalization by Controlling Label-Noise Information in Neural Network WeightsCode1
(Almost) No Label No Cry—0
A Limitation of the PAC-Bayes Framework—0
Adversarial Networks and Autoencoders: The Primal-Dual Relationship and Generalization Bounds—0
Algorithms for Learning Kernels Based on Centered Alignment—0
Algorithmic Stability of Stochastic Gradient Descent with Momentum under Heavy-Tailed Noise—0
Adversarial Multiple Source Domain Adaptation—0
A Convex Relaxation Approach to Generalization Analysis for Parallel Positively Homogeneous Networks—0
Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions—0
Algorithm-Dependent Generalization Bounds for Overparameterized Deep Residual Networks—0
Adaptive Metric Dimensionality Reduction—0
Adaptive Data Analysis for Growing Data—0
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