Lectures related to Adversarial machine learning

Deep Learning: Convolutional Neural Networks

Covers Convolutional Neural Networks, standard architectures, training techniques, and adversarial examples in deep learning.

Sensorimotor Contingency: Amir Zamir

By Amir Zamir explores sensorimotor contingency, intelligence without representation, curriculum learning, and machine learning strategies.

Fine-Grained Visual Categorization: Challenges and Solutions

Explores challenges and solutions in fine-grained visual categorization, focusing on computer vision and machine learning.

Non-Conceptual Knowledge Systems

Delves into the impact of deep learning on non-conceptual knowledge systems and the advancements in transformers and generative adversarial networks.

Socially-aware Artificial Intelligence for Last-mile Mobility

Explores socially-aware AI for last-mile mobility, focusing on understanding social etiquettes, anticipating behaviors, and forecasting crowd movements.

Ethics in AI: A Deep Dive

Explores the ethical implications of AI, emphasizing transparency and accountability in its applications.