convex optimization

Contextual bandits with concave rewards, and an application to fair ranking ICLR 2023 Continuous-time Analysis of Anchor Acceleration NeurIPS 2023 Convex Bounds on the Softmax Function with Applications to Robustness Verification AISTATS 2023 CORNN: Convex optimization of recurrent neural networks for rapid inference of neural dynamics NeurIPS 2023 Dataset Distillation with Convexified Implicit Gradients ICML 2023 Distributed Projection-Free Online Learning for Smooth and Convex Losses AAAI 2023 DoG is SGD’s Best Friend: A Parameter-Free Dynamic Step Size Schedule ICML 2023 DoWG Unleashed: An Efficient Universal Parameter-Free Gradient Descent Method NeurIPS 2023 Efficient Convex Optimization Requires Superlinear Memory (Extended Abstract) IJCAI 2023 Essential Matrix Estimation using Convex Relaxations in Orthogonal Space ICCV 2023 Exact Inference in High-order Structured Prediction ICML 2023 Fast and Interpretable Dynamics for Fisher Markets via Block-Coordinate Updates AAAI 2023 Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective ICML 2023 Faster Differentially Private Convex Optimization via Second-Order Methods NeurIPS 2023 Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case NeurIPS 2023 FedExP: Speeding Up Federated Averaging via Extrapolation ICLR 2023 First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities NeurIPS 2023 Fisher-Legendre (FishLeg) optimization of deep neural networks ICLR 2023 Fixing the NTK: From Neural Network Linearizations to Exact Convex Programs NeurIPS 2023 Globally Optimal Training of Neural Networks with Threshold Activation Functions ICLR 2023 Global optimality for Euclidean CCCP under Riemannian convexity ICML 2023 Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy NeurIPS 2023 Group SLOPE Penalized Low-Rank Tensor Regression JMLR 2023 How to Trust Your Diffusion Model: A Convex Optimization Approach to Conformal Risk Control ICML 2023 Improving the Privacy and Practicality of Objective Perturbation for Differentially Private Linear Learners NeurIPS 2023