Structures in Non-Convex Optimization

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Variance Reduction in Deep Learning

Explores variance reduction techniques in deep learning, covering gradient descent, stochastic gradient descent, SVRG method, and performance comparison of algorithms.

Deep Learning: Data Representations and Neural Networks

Covers data representations, Bag of Words, histograms, data pre-processing, and neural networks.

Adversarial Machine Learning: Fundamentals and Techniques

Explores adversarial machine learning, covering the generation of adversarial examples, robustness challenges, and techniques like Fast Gradient Sign Method.

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Generalization in Deep Learning

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Adaptive Optimization Methods: Theory and Applications

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Deep Learning: Convolutional Neural Networks

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Deep Learning Fundamentals

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