IEMS 458: Convex Optimization VIEW ALL COURSE TIMES AND SESSIONS Prerequisites 450-2 is recommended but not required Description The course will take an in-depth look at the main concepts and ...

Co., Ltd. recently submitted a patent application titled "An Optimization Method, Device, and Medium for Circuit Break Prevention in AI Computing Architecture." This patent focuses on addressing ...

Various non-convex optimization algorithms are thus designed to seek an optimal solution by introducing different constraints, frameworks, and initializations.

This article presents an algorithm design framework for general linearly constrained convex optimization problems. Our approach offers a flexible framework to analyze and design various methods, ...

The portfolio optimization model has limited impact in practice because of estimation issues when applied to real data. To address this, we adapt two machine learning methods, regularization and cross ...

Various non-convex optimization algorithms are thus designed to seek an optimal solution by introducing different constraints, frameworks, and initializations.

Rice University computer scientist Anastasios Kyrillidis has won a National Science Foundation CAREER Award to explore the theory and design of non-convex optimization algorithms, an increasingly ...

Even without convexity, this algorithm can be generically used as an oracle-efficient optimization algorithm, with accuracy evaluated empirically. We complement our theoretical results with an ...