Category - Geoffrey Hinton

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 16.2 — Hierarchical Coordinate Frames [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 16.1 — Learning a joint model of images and captions [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 15.6 — Shallow autoencoders for pre-training [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 15.5 — Learning binary codes for image retrieval [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 15.4 — Semantic Hashing [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 15.3 — Deep autoencoders for document retrieval [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 15.2 — Deep autoencoders [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 9.2 — Limiting the size of the weights [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 14.5 — RBMs are infinite sigmoid belief nets [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 14.4 — Modeling real valued data with an RBM [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 14.3 — Discriminative fine tuning [Neural Networks for Machine Learning]

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AI Science, Geoffrey Hinton, Neural Network, University AI

Lecture 14.2 — Discriminative learning for DBNs [Neural Networks for Machine Learning]