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Tutorial on Probabilistic Topic Modeling: Additive Regularization for Stochastic Matrix Factorization.

, and . AIST, volume 436 of Communications in Computer and Information Science, page 29-46. Springer, (2014)

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Compressive Transformers for Long-Range Sequence Modelling., , , , and . ICLR, OpenReview.net, (2020)Multi-agent Communication meets Natural Language: Synergies between Functional and Structural Language Learning., , and . ACL, page 7663-7674. Association for Computational Linguistics, (2020)Additive regularization of topic models., and . Mach. Learn., 101 (1-3): 303-323 (2015)Additive Regularization of Topic Models for Topic Selection and Sparse Factorization., , and . SLDS, volume 9047 of Lecture Notes in Computer Science, page 193-202. Springer, (2015)Structural and functional learning for learning language use., , and . ViGIL@NeurIPS, (2019)Tutorial on Probabilistic Topic Modeling: Additive Regularization for Stochastic Matrix Factorization., and . AIST, volume 436 of Communications in Computer and Information Science, page 29-46. Springer, (2014)Compressive Transformers for Long-Range Sequence Modelling., , , and . CoRR, (2019)Interpretable probabilistic embeddings: bridging the gap between topic models and neural networks., , and . CoRR, (2017)Probabilistic Approach for Embedding Arbitrary Features of Text.. AIST, volume 11179 of Lecture Notes in Computer Science, page 134-140. Springer, (2018)Robust PLSA Performs Better Than LDA., and . ECIR, volume 7814 of Lecture Notes in Computer Science, page 784-787. Springer, (2013)