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AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC.

, , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 2142-2152. PMLR, (2020)

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Long-tailed Classification from a Bayesian-decision-theory Perspective., and . CoRR, (2023)Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees., and . NeurIPS, page 4923-4932. (2019)Analysis of Climate Campaigns on Social Media using Bayesian Model Averaging., , and . AIES, page 15-25. ACM, (2023)Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent., , and . NeurIPS, (2022)Rethinking Data Distillation: Do Not Overlook Calibration., , , , , , and . ICCV, page 4912-4922. IEEE, (2023)AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC., , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 2142-2152. PMLR, (2020)Balance is Essence: Accelerating Sparse Training via Adaptive Gradient Correction., , , , and . CoRR, (2023)Large Scale Sparse Clustering., and . IJCAI, page 2336-2342. IJCAI/AAAI Press, (2016)Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation., , , , and . AISTATS, volume 206 of Proceedings of Machine Learning Research, page 7288-7310. PMLR, (2023)A Langevin-like Sampler for Discrete Distributions., , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 26375-26396. PMLR, (2022)