Introduction to Online Convex Optimization and Application of Online Portfolio Selection
王嘉澤先生臺灣大學與中央研究院資料科學學位學程博士班 15:30 – 17:00 鴻經館 M107
Abstract：
In this talk, we will explore machine learning and convex optimization problems from the perspective of online convex optimization (OCO). OCO plays a multi-round game between Learner and Reality, with the objective of minimizing regret. Importantly, both machine learning and convex optimization problems can be formulated as OCO problems. We will focus on Follow-the-Regularized-Leader (FTRL) type algorithms. To conclude, we will delve into a classic problem within this framework: online portfolio selection.
20231207演講_ 王嘉澤先生 (臺灣大學與中央研究院資料科學學位學程博士班)