14 Csc2535 PPTs View free & download

CSC2535 Lecture 12 Learning Multiplicative Interactions PowerPoint PPT Presentation

CSC2535 Lecture 12 Learning Multiplicative Interactions - The outer-product of the style and content vectors determines a set of ... Then analytically fit the basis vectors with the style and pose vectors fixed. ...

The outer-product of the style and content vectors determines a set of ... Then analytically fit the basis vectors with the style and pose vectors fixed. ...

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CSC2535: Computation in Neural Networks Lecture 1: The history of neural networks PowerPoint PPT Presentation

CSC2535: Computation in Neural Networks Lecture 1: The history of neural networks - CSC2535: Computation in Neural Networks Lecture 1: The history of neural networks Geoffrey Hinton All lecture s are available as .ppt, .ps, & .htm at

CSC2535: Computation in Neural Networks Lecture 1: The history of neural networks Geoffrey Hinton All lecture s are available as .ppt, .ps, & .htm at

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CSC2535 Lecture 2: Some examples of backpropagation learning PowerPoint PPT Presentation

CSC2535 Lecture 2: Some examples of backpropagation learning - Train the net until it has an 'island of competence' around the prototype. ... LS 0. LS 1. LS 9. 10 squared pixel errors. 10 trajectory prior scores. 10 ...

Train the net until it has an 'island of competence' around the prototype. ... LS 0. LS 1. LS 9. 10 squared pixel errors. 10 trajectory prior scores. 10 ...

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CSC2535: Advanced Machine Learning Lecture 6a Convolutional neural networks for hand-written digit recognition PowerPoint PPT Presentation

CSC2535: Advanced Machine Learning Lecture 6a Convolutional neural networks for hand-written digit recognition - CSC2535: Advanced Machine Learning Lecture 6a Convolutional neural networks for hand-written digit recognition Geoffrey Hinton * The replicated feature approach ...

CSC2535: Advanced Machine Learning Lecture 6a Convolutional neural networks for hand-written digit recognition Geoffrey Hinton * The replicated feature approach ...

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CSC2535: Computation in Neural Networks Lecture 8: Hopfield nets PowerPoint PPT Presentation

CSC2535: Computation in Neural Networks Lecture 8: Hopfield nets - ... of binary threshold units with recurrent connections are very hard to analyse. ... And can we analyze what unlearning achieves? Wishful thinking? ...

... of binary threshold units with recurrent connections are very hard to analyse. ... And can we analyze what unlearning achieves? Wishful thinking? ...

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CSC2535: Advanced Machine Learning Lecture 11 Learning by maximizing agreement between outputs PowerPoint PPT Presentation

CSC2535: Advanced Machine Learning Lecture 11 Learning by maximizing agreement between outputs - It is invariant over time. Its angular momentum also stays the same if it is in free fall. ... Use three consecutive time frames from a fake video sequence as ...

It is invariant over time. Its angular momentum also stays the same if it is in free fall. ... Use three consecutive time frames from a fake video sequence as ...

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CSC2535 Lecture 4 Boltzmann Machines, Sigmoid Belief Nets and Gibbs sampling PowerPoint PPT Presentation

CSC2535 Lecture 4 Boltzmann Machines, Sigmoid Belief Nets and Gibbs sampling - CSC2535 Lecture 4 Boltzmann Machines, Sigmoid Belief Nets and Gibbs sampling Geoffrey Hinton Another computational role for Hopfield nets Instead of using the net to ...

CSC2535 Lecture 4 Boltzmann Machines, Sigmoid Belief Nets and Gibbs sampling Geoffrey Hinton Another computational role for Hopfield nets Instead of using the net to ...

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CSC2535: Advanced Machine Learning Lecture 11b Adaptation at multiple time-scales PowerPoint PPT Presentation

CSC2535: Advanced Machine Learning Lecture 11b Adaptation at multiple time-scales - CSC2535: Advanced Machine Learning Lecture 11b Adaptation at multiple time-scales Geoffrey Hinton * * * * * * * * * * * An overview of how biology solves search ...

CSC2535: Advanced Machine Learning Lecture 11b Adaptation at multiple time-scales Geoffrey Hinton * * * * * * * * * * * An overview of how biology solves search ...

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CSC2535: Computation in Neural Networks Lecture 7: Independent Components Analysis PowerPoint PPT Presentation

CSC2535: Computation in Neural Networks Lecture 7: Independent Components Analysis - Filter the data linearly and then applying a non-linear 'squashing' function. ... So treat the derivative of the squashing function as the prior density. ...

Filter the data linearly and then applying a non-linear 'squashing' function. ... So treat the derivative of the squashing function as the prior density. ...

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CSC2535: Computation in Neural Networks Lecture 11: Conditional Random Fields PowerPoint PPT Presentation

CSC2535: Computation in Neural Networks Lecture 11: Conditional Random Fields - The visible units are clamped in the positive phase and unclamped in the ... Given a string of words, the part-of-speech labels cannot be decided independently. ...

The visible units are clamped in the positive phase and unclamped in the ... Given a string of words, the part-of-speech labels cannot be decided independently. ...

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CSC2535: Computation in Neural Networks Lecture 1b: Learning without hidden units' PowerPoint PPT Presentation

CSC2535: Computation in Neural Networks Lecture 1b: Learning without hidden units' - The neuron has a real-valued output which is a weighted sum of its inputs ... If the output unit incorrectly outputs a zero, add the input vector to the weight vector. ...

The neuron has a real-valued output which is a weighted sum of its inputs ... If the output unit incorrectly outputs a zero, add the input vector to the weight vector. ...

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CSC2535: Computation in Neural Networks Lecture 11 Extracting coherent properties by maximizing mutu PowerPoint PPT Presentation

CSC2535: Computation in Neural Networks Lecture 11 Extracting coherent properties by maximizing mutu - ... 11. Extracting coherent properties by maximizing mutual ... Properties that are invariant over time are usually interesting. Spatially invariant properties ...

... 11. Extracting coherent properties by maximizing mutual ... Properties that are invariant over time are usually interesting. Spatially invariant properties ...

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CSC2535: Lecture 3: Ways to make backpropagation generalize better, and ways to do without a supervision signal. PowerPoint PPT Presentation

CSC2535: Lecture 3: Ways to make backpropagation generalize better, and ways to do without a supervision signal. - The Bayesian framework The Bayesian framework assumes that we ... The Bayesian interpretation of weight decay Full Bayesian Learning Instead of trying to find the ...

The Bayesian framework The Bayesian framework assumes that we ... The Bayesian interpretation of weight decay Full Bayesian Learning Instead of trying to find the ...

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CSC2535: Computation in Neural Networks Lecture 13: Representing things with neurons PowerPoint PPT Presentation

CSC2535: Computation in Neural Networks Lecture 13: Representing things with neurons - Big, yellow, Volkswagen. Do we have a neuron for this combination ... How is it related to the neurons for big and yellow and Volkswagen? Consider a visual scene ...

Big, yellow, Volkswagen. Do we have a neuron for this combination ... How is it related to the neurons for big and yellow and Volkswagen? Consider a visual scene ...

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Csc2535 PowerPoint PPT Presentations