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Text Understanding from Scratch

, and . (2015)cite arxiv:1502.01710Comment: This technical report is superseded by a paper entitled "Character-level Convolutional Networks for Text Classification", arXiv:1509.01626. It has considerably more experimental results and a rewritten introduction.

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Boosting and Other Machine Learning Algorithms., , , , and . ICML, page 53-61. Morgan Kaufmann, (1994)Open Problem: The landscape of the loss surfaces of multilayer networks., , and . COLT, volume 40 of JMLR Workshop and Conference Proceedings, page 1756-1760. JMLR.org, (2015)Binary embeddings with structured hashed projections., , , , , and . ICML, volume 48 of JMLR Workshop and Conference Proceedings, page 344-353. JMLR.org, (2016)Universum Prescription: Regularization using Unlabeled Data., and . CoRR, (2015)A multirange architecture for collision-free off-road robot navigation., , , , , , , , and . J. Field Robotics, 26 (1): 52-87 (2009)Disentangling factors of variation in deep representation using adversarial training., , , , and . NIPS, page 5041-5049. (2016)Adversarially Regularized Autoencoders for Generating Discrete Structures, , , , and . arXiv preprint arXiv:1706.04223, (2017)The need for open source software in machine learning, , , , , , , , , and . Made available in DSpace on 2010-12-20T06: 05: 49Z (GMT). No. of bitstreams: 1 Sonnenburg\_Need2007. pdf: 1278865 bytes, checksum: 31b77a03c5967cafb7381eee2f47fe56 (MD5) Previous issue date: 2009-05-22T01: 55: 10Z, (2007)Universum Prescription: Regularization Using Unlabeled Data., and . AAAI, page 2907-2913. AAAI Press, (2017)Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors., , , , , , and . NeurIPS, (2022)