algorithmic stability

Algorithmic Instabilities of Accelerated Gradient Descent NeurIPS 2021 Algorithmic stability and generalization of an unsupervised feature selection algorithm NeurIPS 2021 Fine-grained Generalization Analysis of Structured Output Prediction IJCAI 2021 Generalization of Model-Agnostic Meta-Learning Algorithms: Recurring and Unseen Tasks NeurIPS 2021 Machine Unlearning via Algorithmic Stability COLT 2021 On Data Efficiency of Meta-learning AISTATS 2021 On the Algorithmic Stability of Adversarial Training NeurIPS 2021 Optimal Rates for Random Order Online Optimization NeurIPS 2021 Sharper Generalization Bounds for Learning with Gradient-dominated Objective Functions ICLR 2021 Stability and Generalization for Randomized Coordinate Descent IJCAI 2021 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 Time-independent Generalization Bounds for SGLD in Non-convex Settings NeurIPS 2021 Toward Better Generalization Bounds with Locally Elastic Stability ICML 2021 Train simultaneously, generalize better: Stability of gradient-based minimax learners ICML 2021 Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent ICML 2020 Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent JMLR 2020 On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning ICLR 2020 An Exponential Tail Bound for the Deleted Estimate AAAI 2019 Capacity Bounded Differential Privacy NeurIPS 2019 High probability generalization bounds for uniformly stable algorithms with nearly optimal rate COLT 2019 Multitask Metric Learning: Theory and Algorithm AISTATS 2019 Online Learning via the Differential Privacy Lens NeurIPS 2019 Private Stochastic Convex Optimization with Optimal Rates NeurIPS 2019