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Sampling for Bayesian Mixture Models: MCMC with Polynomial-Time Mixing., , , , and . CoRR, (2019)Optimal Rates for Zero-Order Convex Optimization: The Power of Two Function Evaluations., , , and . IEEE Trans. Inf. Theory, 61 (5): 2788-2806 (2015)Challenges with EM in application to weakly identifiable mixture models., , , , , and . CoRR, (2019)Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients., , , and . CoRR, (2019)Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems., , , , , and . AISTATS, volume 89 of Proceedings of Machine Learning Research, page 2916-2925. PMLR, (2019)Geographic gossip: efficient aggregation for sensor networks., , and . IPSN, page 69-76. ACM, (2006)Vaidya walk: A sampling algorithm based on the volumetric barrier., , , and . Allerton, page 1220-1227. IEEE, (2017)MAP estimation via agreement on trees: message-passing and linear programming., , and . IEEE Trans. Inf. Theory, 51 (11): 3697-3717 (2005)Early Stopping for Kernel Boosting Algorithms: A General Analysis With Localized Complexities., , and . IEEE Trans. Inf. Theory, 65 (10): 6685-6703 (2019)Information-theoretic limits on sparse support recovery: Dense versus sparse measurements., , and . ISIT, page 2197-2201. IEEE, (2008)