Probability

Calibrated Adaptive Probabilistic ODE Solvers AISTATS 2021 Capturing Delayed Feedback in Conversion Rate Prediction via Elapsed-Time Sampling AAAI 2021 Cascade Size Distributions: Why They Matter and How to Compute Them Efficiently AAAI 2021 Completing the Picture: Randomized Smoothing Suffers from the Curse of Dimensionality for a Large Family of Distributions AISTATS 2021 Compressed Maximum Likelihood ICML 2021 Concentration inequalities under sub-Gaussian and sub-exponential conditions NeurIPS 2021 Concentration of Non-Isotropic Random Tensors with Applications to Learning and Empirical Risk Minimization COLT 2021 Consistent estimation of small masses in feature sampling JMLR 2021 Context-Aware Online Collective Inference for Templated Graphical Models ICML 2021 ConvexVST: A Convex Optimization Approach to Variance-stabilizing Transformation ICML 2021 Correlated Stochastic Block Models: Exact Graph Matching with Applications to Recovering Communities NeurIPS 2021 Cumulants of Hawkes Processes are Robust to Observation Noise ICML 2021 Detection of Signal in the Spiked Rectangular Models ICML 2021 Deterministic Finite-Memory Bias Estimation COLT 2021 Dimension-free empirical entropy estimation NeurIPS 2021 Directed Probabilistic Watershed NeurIPS 2021 Dynamic Cutset Networks AISTATS 2021 Dynamics of Stochastic Momentum Methods on Large-scale, Quadratic Models NeurIPS 2021 Efficient sampling from the Bingham distribution ALT 2021 Efficient Statistics for Sparse Graphical Models from Truncated Samples AISTATS 2021 Equitable and Optimal Transport with Multiple Agents AISTATS 2021 Evaluating the Implicit Midpoint Integrator for Riemannian Hamiltonian Monte Carlo ICML 2021 Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions NeurIPS 2021 Fast and Smooth Interpolation on Wasserstein Space AISTATS 2021 Fast Approximation of the Sliced-Wasserstein Distance Using Concentration of Random Projections NeurIPS 2021