Online Learning and Bandits - Part 1
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore the fundamentals of online learning and bandit algorithms in this comprehensive lecture from the Theory of Reinforcement Learning Boot Camp. Delve into key concepts such as full information online learning, online gradient descent, exponential weights algorithm, and follow the regularized leader. Examine the balance between model complexity and overfitting, and discover applications in offline optimization and computing saddle points. Learn from experts Alan Malek of DeepMind and Wouter Koolen from Centrum Wiskunde & Informatica as they guide you through working definitions, design principles, and performance analyses of various algorithms. Gain valuable insights into the theoretical foundations of reinforcement learning and their practical implications in this hour-long presentation.