under construction.
•Deep learning
•Why deep learning?
•State of Art deep learning
•Parallel Deep Learning at Google
•Sparse coding
•Dictionary learning
•Multiple Layer NN (MLP)
•Convolutional Neural Network
•Stacked Denoising Auto-Encoder
•Deep Belief Nets (DBN)
•Deep Boltzmann Machines (DBM)
•Generative model: MRF
•Deep Gated MRF
•Image Denoising
•Image Denoising by BM3D
•Image Denoising by K-SVD
•Image Denoising by CNN
•Image Denoising by MLPs
•Image Denoising by DBMs
•Image Denoising by Deep GMRF
•Image Restoration by CNN
•Image Super-resolution
•Example-based SR
•Sparse Coding for SR
•Frame Alignment-based SR
•Image Super-resolution by DBMs
•Image Super-resolution by DBNs
•Image SR by Cascaded SAE
•Image SR by Deep CNN
•References
•Appendix
•PCA, AP & Spectral Clustering
•NMF & pLSA
•ISOMAP
•LLE
•Laplacian Eigenmaps
•Gaussian Mixture & EM
•Hidden Markov Model
•Discriminative model: CRF
•Product of Experts
•Back propagation
•Stochastic gradient descent
•MCMC sampling for optimization approx.
•Mean field for optim. approx.
•Contrastive divergence
•“Wake-sleep” algorithm
•Two-stage pre-training
•Greedy layer-wise unsupervised pre-training