开课单位--美国NEC实验室
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Deep Learning for Efficient Discriminative Parsing[高效识别分析的深层学习]
  Ronan Collobert(美国NEC实验室) We propose a new fast purely discriminative algorithm for natural language parsing, based on a "deep" recurrent convolutional graph transfor...
热度:25

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Large-Scale Semi-Supervised Learning[大规模半监督学习]
  Jason Weston(美国NEC实验室) Labeling data is expensive, whilst unlabeled data is often abundant and cheap to collect. Semi-supervised learning algorithms that can use both types ...
热度:43

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Learning using Many Examples[学习使用许多例子]
  Léon Bottou(美国NEC实验室) The statistical learning theory suggests to choose large capacity models that barely avoid over-fitting the training data. In that perspective, all da...
热度:43

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A Unified Architecture for Natural Language Processing: Deep Neural Networks with Multitask Learning[自然语言处理的统一架构:多任务学习的深度神经网络]
  Ronan Collobert(美国NEC实验室) We describe a single convolutional neural network architecture that given a sentence, outputs a host of language processing predictions: part-of-speec...
热度:91

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Torch[火炬]
  Ronan Collobert(美国NEC实验室) Torch provides a Matlab-like environment for state-of-the-art machine learning algorithms. It is easy to use and very efficient, thanks to a simple-yet...
热度:88

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Deep Learning for Efficient Discriminative Parsing[基于深度学习的区分性句法分析]
  Ronan Collobert(美国NEC实验室) We propose a new fast purely discriminative algorithm for natural language parsing, based on a "deep" recurrent convolutional graph transfor...
热度:34

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Large-Scale Collaborative Prediction Using a Nonparametric Random Effects Model[基于非参数随机效应模型的大规模协同预测]
  Kai Yu(美国NEC实验室) A nonparametric model is introduced that allows multiple related regression tasks to take inputs from a common data space. Traditional transfer learni...
热度:70
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