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projects:sgd [leon.bottou.org]
Learning algorithms based on Stochastic Gradient approximations are known for their poor performance on optimization tasks and their extremely good performance on machine learning tasks (Bottou and Bousquet, 2008). Despite these proven capabilities, there were lingering concerns about the difficulty of setting the adaptation gains and achieving robust performance. Stochastic gradient algorithms ha
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Lightly Supervised Learning of Text Normalization: Russian Number Names Abstract Most areas of natural language pro- cessing today make heavy use of au- tomatic inference from large corpora. One exception is text-normalization for such applications as te
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