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The Segmented iHMM: A Simple, Efficient Hierarchical Infinite HMM.

, , , and . ICML, volume 48 of JMLR Workshop and Conference Proceedings, page 2682-2691. JMLR.org, (2016)

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Computational caches., , , , , , and . SYSTOR, page 8:1-8:7. ACM, (2013)Learning the Parameters of Determinantal Point Process Kernels., , , and . ICML, volume 32 of JMLR Workshop and Conference Proceedings, page 1224-1232. JMLR.org, (2014)Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks., and . ICML, volume 37 of JMLR Workshop and Conference Proceedings, page 1861-1869. JMLR.org, (2015)Bayesian Learning and Inference in Recurrent Switching Linear Dynamical Systems., , , , , and . AISTATS, volume 54 of Proceedings of Machine Learning Research, page 914-922. PMLR, (2017)Variability and predictability in tactile sensing during grasping., , and . ICRA, page 158-164. IEEE, (2016)Firefly Monte Carlo: Exact MCMC with Subsets of Data., and . UAI, page 543-552. AUAI Press, (2014)Dependent Multinomial Models Made Easy: Stick-Breaking with the Polya-gamma Augmentation., , and . NIPS, page 3456-3464. (2015)Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability., , , , , and . NeurIPS, page 25502-25515. (2021)On Warm-Starting Neural Network Training., and . NeurIPS, (2020)Learning Composable Energy Surrogates for PDE Order Reduction., , , , and . NeurIPS, (2020)