Lectures related to Boltzmann machine

Convolutional Neural Networks

Covers Convolutional Neural Networks, including layers, training strategies, standard architectures, tasks like semantic segmentation, and deep learning tricks.

Adversarial Machine Learning

Explores adversarial machine learning, generative adversarial networks, and the challenges of adversarial examples in data optimization.

Adversarial Training: Optimization and Applications

Explores adversarial training optimization, practical implementation, interpretability, fairness, Wasserstein distance, and Wasserstein GANs.

Learning Sparse Features: Overfitting in Neural Networks

Discusses how learning sparse features can lead to overfitting in neural networks despite empirical evidence of generalization.