Neural Networks 1 Hidden Layer Neural Networks A

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Neural Networks

Neural Networks

1 -Hidden Layer Neural Networks A two-stage regression or classification model

1 -Hidden Layer Neural Networks A two-stage regression or classification model

Least Square Fitting: Backpropogation (BP) 平方误差损失的反向传播细节 具有导数（Chain Rule for Composite Functions)

Least Square Fitting: Backpropogation (BP) 平方误差损失的反向传播细节 具有导数（Chain Rule for Composite Functions)

Example: Hand-written Digits

Example: Hand-written Digits

五种Network

五种Network

五种Network Structures

五种Network Structures

Test Performance

Test Performance

Test Performance

Test Performance

Deep Learning? 多层神经网络？Hierarchical Features? IPAM-UCLA 2012 Summer School: Deep Learning, Feature Learning: http: //www.

Deep Learning? 多层神经网络？Hierarchical Features? IPAM-UCLA 2012 Summer School: Deep Learning, Feature Learning: http: //www. ipam. ucla. edu/programs/gss 2012/ contains various video streams and slides Andrew Ng’s course at Stanford, Unsupervised Feature Learning and Deep Learning: http: //ufldl. stanford. edu/wiki/index. php/UFLDL_Tutorial

Deep vs. Shallow Learning as Matrix Factorization: SVD: orthogonal B, C Topic models: nonnegative

Deep vs. Shallow Learning as Matrix Factorization: SVD: orthogonal B, C Topic models: nonnegative B, C Sparse coding/dictionary learning: B is dictionary (basis, frame, etc. ), C is sparse Conditional independence:

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