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Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients., , , , and . NeurIPS, (2022)Stochastic Approximation with Biased MCMC for Expectation Maximization., , , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 2332-2340. PMLR, (2024)Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing?, , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 235-243. PMLR, (2024)Provably Scalable Black-Box Variational Inference with Structured Variational Families., , , and . ICML, OpenReview.net, (2024)Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 16853-16876. PMLR, (2023)Approximation-Aware Bayesian Optimization., , , , , and . CoRR, (2024)The Behavior and Convergence of Local Bayesian Optimization., , , and . NeurIPS, (2023)Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing?, , and . CoRR, (2023)Black-Box Variational Inference Converges., , , , and . CoRR, (2023)On the Convergence of Black-Box Variational Inference., , , , and . NeurIPS, (2023)