Probability

Approximate Inference of Outcomes in Probabilistic Elections AAAI 2019 Approximate Profile Maximum Likelihood JMLR 2019 Approximating the Permanent by Sampling from Adaptive Partitions NeurIPS 2019 A Representer Theorem for Deep Kernel Learning JMLR 2019 Asymptotics for Sketching in Least Squares Regression NeurIPS 2019 Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with double power-law behavior ICML 2019 Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization NeurIPS 2019 Complexity of Fundamental Problems in Probabilistic Abstract Argumentation: Beyond Independence (Extended Abstract) IJCAI 2019 Concentration Inequalities for Conditional Value at Risk ICML 2019 Concentration of risk measures: A Wasserstein distance approach NeurIPS 2019 Database Alignment with Gaussian Features AISTATS 2019 Deep Signature Transforms NeurIPS 2019 Determinantal Point Processes for Coresets JMLR 2019 Disagreement-Based Combinatorial Pure Exploration: Sample Complexity Bounds and an Efficient Algorithm COLT 2019 DPPy: DPP Sampling with Python JMLR 2019 Efficient Optimal Approximation of Discrete Random Variables for Estimation of Probabilities of Missing Deadlines AAAI 2019 Elliptical Perturbations for Differential Privacy NeurIPS 2019 Estimating Convergence of Markov chains with L-Lag Couplings NeurIPS 2019 Estimating the Mixing Time of Ergodic Markov Chains COLT 2019 Estimation of smooth densities in Wasserstein distance COLT 2019 Fast Algorithm for Generalized Multinomial Models with Ranking Data ICML 2019 Faster Algorithms for High-Dimensional Robust Covariance Estimation COLT 2019 Fast Mean Estimation with Sub-Gaussian Rates COLT 2019 Flexible Modeling of Diversity with Strongly Log-Concave Distributions NeurIPS 2019 Gain estimation of linear dynamical systems using Thompson Sampling AISTATS 2019