Probability

Faster and Better Simple Temporal Problems AAAI 2021 Fast PCA in 1-D Wasserstein Spaces via B-splines Representation and Metric Projection AAAI 2021 Finding Relevant Information via a Discrete Fourier Expansion ICML 2021 Flow-based Alignment Approaches for Probability Measures in Different Spaces AISTATS 2021 Generalized Kings and Single-Elimination Winners in Random Tournaments IJCAI 2021 Hoeffding's Inequality for General Markov Chains and Its Applications to Statistical Learning JMLR 2021 Hypothesis testing with low-degree polynomials in the Morris class of exponential families COLT 2021 Implicit Langevin Algorithms for Sampling From Log-concave Densities JMLR 2021 Impossibility of Partial Recovery in the Graph Alignment Problem COLT 2021 Improved Complexity Bounds in Wasserstein Barycenter Problem AISTATS 2021 Inference of Black Hole Fluid-Dynamics From Sparse Interferometric Measurements ICCV 2021 Infinite-Dimensional Fisher Markets: Equilibrium, Duality and Optimization AAAI 2021 Instance-Dependent Bounds for Zeroth-order Lipschitz Optimization with Error Certificates NeurIPS 2021 Interpretable Stein Goodness-of-fit Tests on Riemannian Manifold ICML 2021 Ising Model Selection Using ℓ_1-Regularized Linear Regression: A Statistical Mechanics Analysis NeurIPS 2021 Iterative Connecting Probability Estimation for Networks NeurIPS 2021 It was “all” for “nothing”: sharp phase transitions for noiseless discrete channels COLT 2021 Johnson-Lindenstrauss Transforms with Best Confidence COLT 2021 KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support NeurIPS 2021 Kernel Stein Discrepancy Descent ICML 2021 Kernel Thinning COLT 2021 Large-Scale Wasserstein Gradient Flows NeurIPS 2021 Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions NeurIPS 2021 Learning partial correlation graphs and graphical models by covariance queries JMLR 2021 Learning Partially Observed Linear Dynamical Systems from Logarithmic Number of Samples L4DC 2021