Probability

ROME: Robust Multi-Modal Density Estimator IJCAI 2024 Sample Complexity Bounds for Estimating Probability Divergences under Invariances ICML 2024 Sample-efficient neural likelihood-free Bayesian inference of implicit HMMs AISTATS 2024 Sampling Polytopes with Riemannian HMC: Faster Mixing via the Lewis Weights Barrier COLT 2024 Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss ICML 2024 Shifted Interpolation for Differential Privacy ICML 2024 Sinkhorn Flow as Mirror Flow: A Continuous-Time Framework for Generalizing the Sinkhorn Algorithm AISTATS 2024 Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates ICML 2024 Sliding Down the Stairs: How Correlated Latent Variables Accelerate Learning with Neural Networks ICML 2024 SPABA: A Single-Loop and Probabilistic Stochastic Bilevel Algorithm Achieving Optimal Sample Complexity ICML 2024 Spectral Phase Transition and Optimal PCA in Block-Structured Spiked Models ICML 2024 Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces II: non-compact symmetric spaces JMLR 2024 Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces I: the compact case JMLR 2024 Statistical Spatially Inhomogeneous Diffusion Inference AAAI 2024 Stochastic Quantum Sampling for Non-Logconcave Distributions and Estimating Partition Functions ICML 2024 Structural perspective on constraint-based learning of Markov networks AISTATS 2024 Sum-of-norms clustering does not separate nearby balls JMLR 2024 Testably Learning Polynomial Threshold Functions NeurIPS 2024 Testing Self-Reducible Samplers AAAI 2024 The Moderating Effect of Instant Runoff Voting AAAI 2024 The Privacy Power of Correlated Noise in Decentralized Learning ICML 2024 The Relative Gaussian Mechanism and its Application to Private Gradient Descent AISTATS 2024 Tight Bounds for Local Glivenko-Cantelli ALT 2024 To smooth a cloud or to pin it down: Expressiveness guarantees and insights on score matching in denoising diffusion models UAI 2024 Towards Theoretical Understanding of Learning Large-scale Dependent Data via Random Features ICML 2024