generalization bound

Stability and Generalization of Stochastic Gradient Methods for Minimax Problems ICML 2021 Stability and Risk Bounds of Iterative Hard Thresholding AISTATS 2021 Stability & Generalisation of Gradient Descent for Shallow Neural Networks without the Neural Tangent Kernel NeurIPS 2021 Stable Sample Compression Schemes: New Applications and an Optimal SVM Margin Bound ALT 2021 Surrogate Regret Bounds for Polyhedral Losses NeurIPS 2021 The Effect of the Intrinsic Dimension on the Generalization of Quadratic Classifiers NeurIPS 2021 Tighter Generalization Bounds for Iterative Differentially Private Learning Algorithms UAI 2021 Time-independent Generalization Bounds for SGLD in Non-convex Settings NeurIPS 2021 Toward Better Generalization Bounds with Locally Elastic Stability ICML 2021 Towards a Unified Information-Theoretic Framework for Generalization NeurIPS 2021 Towards Sharper Generalization Bounds for Structured Prediction NeurIPS 2021 Train simultaneously, generalize better: Stability of gradient-based minimax learners ICML 2021 Understanding the Generalization Benefit of Model Invariance from a Data Perspective NeurIPS 2021 Uniform Convergence, Adversarial Spheres and a Simple Remedy ICML 2021 Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds and Benign Overfitting NeurIPS 2021 What training reveals about neural network complexity NeurIPS 2021 Abstraction Mechanisms Predict Generalization in Deep Neural Networks ICML 2020 A Closer Look at the Training Strategy for Modern Meta-Learning NeurIPS 2020 Adapting Neural Architectures Between Domains NeurIPS 2020 Adaptive Adversarial Multi-task Representation Learning ICML 2020 Adversarial Risk Bounds through Sparsity based Compression AISTATS 2020 A Limitation of the PAC-Bayes Framework NeurIPS 2020 Assessing Local Generalization Capability in Deep Models AISTATS 2020 Automated Spectral Kernel Learning AAAI 2020 Beyond Linearization: On Quadratic and Higher-Order Approximation of Wide Neural Networks ICLR 2020