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Interpretable Semantic Vectors from a Joint Model of Brain- and Text- Based Meaning.

, , , and . ACL (1), page 489-499. The Association for Computer Linguistics, (2014)

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Coupling semi-supervised learning of categories and relations, , , and . SemiSupLearn '09: Proceedings of the NAACL HLT 2009 Workshop on Semi-Supervised Learning for Natural Language Processing, page 1--9. Morristown, NJ, USA, Association for Computational Linguistics, (2009)Improving Text Classification by Shrinkage in a Hierarchy of Classes, , , and . ICML, page 359-367. Morgan Kaufmann, (1998)Scoup-SMT: Scalable Coupled Sparse Matrix-Tensor Factorization, , , , , and . CoRR, (2013)Toward Never Ending Language Learning., , , , , , and . AAAI Spring Symposium: Learning by Reading and Learning to Read, page 1-2. AAAI, (2009)The Need for Biases in Learning Generalizations. Rutgers University, New Brunswick, NJ, (1980)Estimating Accuracy from Unlabeled Data: A Bayesian Approach., , and . ICML, volume 48 of JMLR Workshop and Conference Proceedings, page 1416-1425. JMLR.org, (2016)An Analysis of Generalization as a Search Problem.. IJCAI, page 577-582. William Kaufmann, (1979)Machine learning. McGraw-hill New York, (1997)Machine learning classifiers and fMRI: A tutorial overview., , and . NeuroImage, 45 (1): S199-S209 (2009)Turbo-SMT: Accelerating Coupled Sparse Matrix-Tensor Factorizations by 200x., , , , , and . SDM, page 118-126. SIAM, (2014)