log-concave distribution

Convergence of Noise-Free Sampling Algorithms with Regularized Wasserstein Proximals JMLR 2026 Information-Theoretic Guarantees for Recovering Low-Rank Tensors from Symmetric Rank-One Measurements ALT 2025 Regularized Dikin Walks for Sampling Truncated Logconcave Measures, Mixed Isoperimetry and Beyond Worst-Case Analysis COLT 2025 Sampling and Estimation on Manifolds using the Langevin Diffusion JMLR 2025 Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo AISTATS 2024 Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space COLT 2024 Langevin Monte Carlo for strongly log-concave distributions: Randomized midpoint revisited ICLR 2024 Log-concave Sampling from a Convex Body with a Barrier: a Robust and Unified Dikin Walk NeurIPS 2024 Sampling Multimodal Distributions with the Vanilla Score: Benefits of Data-Based Initialization ICLR 2024 Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler COLT 2023 Contrastive Moments: Unsupervised Halfspace Learning in Polynomial Time NeurIPS 2023 Double Randomized Underdamped Langevin with Dimension-Independent Convergence Guarantee NeurIPS 2023 Improved dimension dependence of a proximal algorithm for sampling COLT 2023 Learning Exponential Families from Truncated Samples NeurIPS 2023 On a Class of Gibbs Sampling over Networks COLT 2023 Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave Sampling COLT 2023 Sampling from Structured Log-Concave Distributions via a Soft-Threshold Dikin Walk NeurIPS 2023 Tester-Learners for Halfspaces: Universal Algorithms NeurIPS 2023 Benign Overfitting without Linearity: Neural Network Classifiers Trained by Gradient Descent for Noisy Linear Data COLT 2022 Bounding the Error of Discretized Langevin Algorithms for Non-Strongly Log-Concave Targets JMLR 2022 Differential privacy for symmetric log-concave mechanisms AISTATS 2022 Learning a Single Neuron with Adversarial Label Noise via Gradient Descent COLT 2022 Log-Concave and Multivariate Canonical Noise Distributions for Differential Privacy NeurIPS 2022 Minimax Mixing Time of the Metropolis-Adjusted Langevin Algorithm for Log-Concave Sampling JMLR 2022 Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants NeurIPS 2022