Mathematics & Optimization

No Double Descent in Principal Component Regression: A High-Dimensional Analysis ICML 2024 No Free Lunch Theorem and Black-Box Complexity Analysis for Adversarial Optimisation NeurIPS 2024 No Internal Regret with Non-convex Loss Functions AAAI 2024 Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization ICML 2024 Noisy Dual Mirror Descent: A Near Optimal Algorithm for Jointly-DP Convex Resource Allocation NeurIPS 2024 Non-asymptotic Global Convergence Analysis of BFGS with the Armijo-Wolfe Line Search NeurIPS 2024 Nonasymptotic regret analysis of adaptive linear quadratic control with model misspecification L4DC 2024 Non-clairvoyant Scheduling with Partial Predictions ICML 2024 Non-Convex Joint Community Detection and Group Synchronization via Generalized Power Method AISTATS 2024 Nonconvex Multiview Subspace Clustering Framework with Efficient Method Designs and Theoretical Analysis IJCAI 2024 Nonconvex scenario optimization for data-driven reachability L4DC 2024 Non-convex Stochastic Composite Optimization with Polyak Momentum ICML 2024 Non-geodesically-convex optimization in the Wasserstein space NeurIPS 2024 Nonlinear Filtering with Brenier Optimal Transport Maps ICML 2024 Non-monotone Sequential Submodular Maximization AAAI 2024 Non-Oblivious Performance of Random Projections ACML 2024 Non-parametric classification via expand-and-sparsify representation NeurIPS 2024 Nonparametric Copula Models for Multivariate, Mixed, and Missing Data JMLR 2024 Nonparametric Detection of Gerrymandering in Multiparty Plurality Elections IJCAI 2024 Nonparametric Inference under B-bits Quantization JMLR 2024 Non-parametric Online Change Point Detection on Riemannian Manifolds ICML 2024 Nonparametric Regression for 3D Point Cloud Learning JMLR 2024 Nonsmooth Implicit Differentiation: Deterministic and Stochastic Convergence Rates ICML 2024 Non-splitting Neyman-Pearson Classifiers JMLR 2024 Non-stationary Online Convex Optimization with Arbitrary Delays ICML 2024