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Continuous Optimization

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Vector Quantile Regression on Manifolds AISTATS 2024
Efficient Leverage Score Sampling for Tensor Train Decomposition NIPS 2024
Near-Optimal Convex Simple Bilevel Optimization with a Bisection Method AISTATS 2024
Absence of spurious solutions far from ground truth: A low-rank analysis with high-order losses AISTATS 2024
Optimization Algorithm Design via Electric Circuits NIPS 2024
Constrained Diffusion with Trust Sampling NIPS 2024
Extragradient Type Methods for Riemannian Variational Inequality Problems AISTATS 2024
Unscrambling disease progression at scale: fast inference of event permutations with optimal transport NIPS 2024
Generalization Bounds of Nonconvex-(Strongly)-Concave Stochastic Minimax Optimization AISTATS 2024
Parametric model reduction of mean-field and stochastic systems via higher-order action matching NIPS 2024
Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization NIPS 2024
Light Unbalanced Optimal Transport NIPS 2024
The Solution Path of SLOPE AISTATS 2024
Learning Distributions on Manifolds with Free-Form Flows NIPS 2024
Learning Macroscopic Dynamics from Partial Microscopic Observations NIPS 2024
Accelerating ERM for data-driven algorithm design using output-sensitive techniques NIPS 2024
The Reliability of OKRidge Method in Solving Sparse Ridge Regression Problems NIPS 2024
Sample-Efficient Geometry Reconstruction from Euclidean Distances using Non-Convex Optimization NIPS 2024
Faster Accelerated First-order Methods for Convex Optimization with Strongly Convex Function Constraints NIPS 2024
Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms NIPS 2024
Instance-Optimal Private Density Estimation in the Wasserstein Distance NIPS 2024
Stochastic Newton Proximal Extragradient Method NIPS 2024
Private Geometric Median NIPS 2024
Learning with Fitzpatrick Losses NIPS 2024
Generalized Eigenvalue Problems with Generative Priors NIPS 2024