The Problem Dependant Complexity of Sequential Optimization by Aurélien Garivier

Explore the intricacies of sequential optimization in this 49-minute lecture by Aurélien Garivier at the International Centre for Theoretical Sciences. Delve into the problem-dependent complexity of sequential optimization as part of the "Data Science: Probabilistic and Optimization Methods" discussion meeting. Gain insights into cutting-edge data science techniques, focusing on probabilistic and optimization methods. Learn from leading experts in the field and discover how these approaches are revolutionizing various scientific disciplines. Understand the intersection of pure mathematics and practical applications in data processing and analysis. Benefit from a comprehensive overview of the analytic and algorithmic aspects of data science, ranging from theoretical foundations to heuristic approaches. Engage with content that bridges traditional applied mathematics with modern optimization, linear algebra, and probability and statistics.

The Problem Dependant Complexity of Sequential Optimization by Aurélien Garivier