convergence guarantee

Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence ICML 2022 Mutation-driven follow the regularized leader for last-iterate convergence in zero-sum games UAI 2022 On the Convergence of Continuous Constrained Optimization for Structure Learning AISTATS 2022 On the Effective Number of Linear Regions in Shallow Univariate ReLU Networks: Convergence Guarantees and Implicit Bias NeurIPS 2022 Robust Training of Neural Networks Using Scale Invariant Architectures ICML 2022 SGD with Coordinate Sampling: Theory and Practice JMLR 2022 Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning NeurIPS 2022 The AIM and EM Algorithms for Learning from Coarse Data JMLR 2022 Tight Analysis of Extra-gradient and Optimistic Gradient Methods For Nonconvex Minimax Problems NeurIPS 2022 Towards Practical Adam: Non-Convexity, Convergence Theory, and Mini-Batch Acceleration JMLR 2022 When AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guarantee ICML 2022 Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies ICML 2021 AC-GC: Lossy Activation Compression with Guaranteed Convergence NeurIPS 2021 Advice-Guided Reinforcement Learning in a non-Markovian Environment AAAI 2021 Asynchronous Optimization Methods for Efficient Training of Deep Neural Networks with Guarantees AAAI 2021 Conservative Safety Critics for Exploration ICLR 2021 Convergence Guarantees for Gaussian Process Means With Misspecified Likelihoods and Smoothness JMLR 2021 CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee ICML 2021 Data Augmentation for Text Generation Without Any Augmented Data ACL 2021 Evaluating model performance under worst-case subpopulations NeurIPS 2021 Global Convergence to Local Minmax Equilibrium in Classes of Nonconvex Zero-Sum Games NeurIPS 2021 It Has Potential: Gradient-Driven Denoisers for Convergent Solutions to Inverse Problems NeurIPS 2021 Large Batch Optimization for Deep Learning Using New Complete Layer-Wise Adaptive Rate Scaling AAAI 2021 Learning A Minimax Optimizer: A Pilot Study ICLR 2021 On the Convergence Theory of Debiased Model-Agnostic Meta-Reinforcement Learning NeurIPS 2021