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Application of Deep Belief Networks for Natural Language Understanding.

, , and . IEEE ACM Trans. Audio Speech Lang. Process., 22 (4): 778-784 (2014)

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Modeling High-Dimensional Data by Combining Simple Experts.. AAAI/IAAI, page 1159-1164. AAAI Press / The MIT Press, (2000)Massively Parallel Architectures for AI: NETL, Thistle, and Boltzmann Machines., , and . AAAI, page 109-113. AAAI Press, (1983)Learning Distributed Representations of Concepts Using Linear Relational Embedding., and . IEEE Trans. Knowl. Data Eng., 13 (2): 232-244 (2001)Conditional Restricted Boltzmann Machines for Structured Output Prediction., , and . UAI, page 514-522. AUAI Press, (2011)Dynamical binary latent variable models for 3D human pose tracking., , , and . CVPR, page 631-638. IEEE Computer Society, (2010)Using fast weights to improve persistent contrastive divergence., and . ICML, volume 382 of ACM International Conference Proceeding Series, page 1033-1040. ACM, (2009)Factored conditional restricted Boltzmann Machines for modeling motion style., and . ICML, volume 382 of ACM International Conference Proceeding Series, page 1025-1032. ACM, (2009)Learning to Label Aerial Images from Noisy Data., and . ICML, icml.cc / Omnipress, (2012)Learning distributed representations of concepts, and . Proceedings of the eighth annual conference of the cognitive science society, 1, page 12. Amherst, MA, (1986)Modeling the manifolds of images of handwritten digits., , and . IEEE Trans. Neural Networks, 8 (1): 65-74 (1997)