cs501r_f2016
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| - | Preliminary Syllabus and topics to be covered: | ||
| - | |||
| - | - Basics of DNNs | ||
| - | - Convolution layers | ||
| - | - Maxpooling layers | ||
| - | - Relu units | ||
| - | - Softmax units | ||
| - | - Local response normalization / contrast normalization | ||
| - | - Regularization strategies | ||
| - | - Dropout | ||
| - | - Dropconnect | ||
| - | - Batch normalization | ||
| - | - Adversarial networks | ||
| - | - Data augmentation | ||
| - | - High-level implementation packages - pros and cons | ||
| - | - Tensorflow, Theano, Caffe, Keras, Torch, Mocha | ||
| - | - Case studies / existing networks and why they're interesting | ||
| - | - AlexNet | ||
| - | - VGG | ||
| - | - GoogLeNet / Inception | ||
| - | - ZFNet | ||
| - | - Training & initialization | ||
| - | - Initialization strategies: Xavier, Gaussian, Identity, Sparse | ||
| - | - Optimization theory and algorithms | ||
| - | - Local minima; saddle points; plateaus | ||
| - | - SGD | ||
| - | - RPROP | ||
| - | - RMS prop | ||
| - | - Adagrad | ||
| - | - Adam | ||
| - | - Higher-order algorithms (LBFGS; Hessian-free; trust-region) | ||
| - | - Nesterov and momentum | ||
| - | - Large-scale distributed learning | ||
| - | - Parameter servers | ||
| - | - Asynchronous vs. synchronous architectures | ||
| - | - Temporal networks and how to train them | ||
| - | - Basic RNNs and Backprop-through-time | ||
| - | - LSTMs | ||
| - | - Deep Memory Nets | ||
| - | - Application areas | ||
| - | - Deep reinforcement learning | ||
| - | - NN models of style vs. content (deepart.io) | ||
| - | - Imagenet classification | ||
| - | - The Neural Turing Machine | ||
| - | - Sentiment classification | ||
| - | - Word embeddings | ||
| - | - Understanding and visualizing CNNs | ||
| - | - tSNE embeddings | ||
| - | - deconvnets | ||
| - | - data gradients / inceptionism | ||
| - | - Misc | ||
| - | - Network compression | ||
| - | - Low bit-precision networks | ||
| - | - Sum-product networks | ||
| - | - Evolutionary approaches to topology discovery | ||
| - | - Spatial transformer networks | ||
| - | - Network-in-network | ||
| - | - Regions-with-CNN | ||
cs501r_f2016.txt ยท Last modified: 2021/06/30 23:42 (external edit)
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