Mathematics & Optimization

Abstract Argumentation Frameworks with Marginal Probabilities IJCAI 2022 A causal bandit approach to learning good atomic interventions in presence of unobserved confounders UAI 2022 Accelerated Federated Learning with Decoupled Adaptive Optimization ICML 2022 Accelerated Gradient Methods for Geodesically Convex Optimization: Tractable Algorithms and Convergence Analysis ICML 2022 Accelerated Multiplicative Weights Update Avoids Saddle Points Almost Always IJCAI 2022 Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling NeurIPS 2022 Accelerated Projected Gradient Algorithms for Sparsity Constrained Optimization Problems NeurIPS 2022 Accelerated SGD for Non-Strongly-Convex Least Squares COLT 2022 Accelerating Adaptive Cubic Regularization of Newton's Method via Random Sampling JMLR 2022 Accelerating Model-Free Policy Optimization Using Model-Based Gradient: A Composite Optimization Perspective L4DC 2022 Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion NeurIPS 2022 Accelerating training of batch normalization: A manifold perspective UAI 2022 Acceleration in Distributed Optimization under Similarity AISTATS 2022 Acceleration in Distributed Sparse Regression NeurIPS 2022 Accurate Quantization of Measures via Interacting Particle-based Optimization ICML 2022 Achieving Envy-Freeness with Limited Subsidies under Dichotomous Valuations IJCAI 2022 A Combinatorial Perspective on the Optimization of Shallow ReLU Networks NeurIPS 2022 A Communication-efficient Algorithm with Linear Convergence for Federated Minimax Learning NeurIPS 2022 A competitive analysis of online failure-aware assignment UAI 2022 A Completely Tuning-Free and Robust Approach to Sparse Precision Matrix Estimation ICML 2022 A composable machine-learning approach for steady-state simulations on high-resolution grids NeurIPS 2022 A Computationally Efficient Framework for Vector Representation of Persistence Diagrams JMLR 2022 A consistently adaptive trust-region method NeurIPS 2022 A Continuous Time Framework for Discrete Denoising Models NeurIPS 2022 A Contraction Theory Approach to Optimization Algorithms from Acceleration Flows AISTATS 2022