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Generalization

135 directly classified papers

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Papers

Generalization Bound of Gradient Descent for Non-Convex Metric Learning NIPS 2020
Overfitting Can Be Harmless for Basis Pursuit, But Only to a Degree NIPS 2020
A Closer Look at the Training Strategy for Modern Meta-Learning NIPS 2020
Decision trees as partitioning machines to characterize their generalization properties NIPS 2020
Conditioning and Processing: Techniques to Improve Information-Theoretic Generalization Bounds NIPS 2020
Kernel Alignment Risk Estimator: Risk Prediction from Training Data NIPS 2020
Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization NIPS 2020
Quantifying Generalization in Reinforcement Learning ICML 2019
A Meta-Analysis of Overfitting in Machine Learning NIPS 2019
Margin-Based Generalization Lower Bounds for Boosted Classifiers NIPS 2019
A Necessary and Sufficient Stability Notion for Adaptive Generalization NIPS 2019
Generalization Error Analysis of Quantized Compressive Learning NIPS 2019
Distributionally Robust Optimization and Generalization in Kernel Methods NIPS 2019
Minimizers of the Empirical Risk and Risk Monotonicity NIPS 2019
Uniform convergence may be unable to explain generalization in deep learning NIPS 2019
To Annotate or Not? Predicting Performance Drop under Domain Shift EMNLP 2019
Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds AAAI 2019
Less but Better: Generalization Enhancement of Ordinal Embedding via Distributional Margin AAAI 2019
A Closer Look at Data Bias in Neural Extractive Summarization Models EMNLP 2019
Multi-Class Learning: From Theory to Algorithm NIPS 2018
Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds NIPS 2018
Chaining Mutual Information and Tightening Generalization Bounds NIPS 2018
The Limits of Post-Selection Generalization NIPS 2018
Adversarially Robust Generalization Requires More Data NIPS 2018
On Optimal Generalizability in Parametric Learning NIPS 2017