Solving complex optimization problems is central to many modern technologies, from logistics and financial modeling to chip ...
The Sports Analytics Research Group employs quantitative analysis to give teams the hard numbers they need to perform better ...
Abstract: Software-defined network (SDN) controllers include mechanisms to globally reconfigure the network in order to respond to a changing environment. As demands arrive or leave the system, the ...
Learn machine learning from the ground up - using Python and a handful of fundamental tools. This repository contains a range of resources associated with the 2nd edition of the university textbook ...
In this work, we address a question that has attracted intense interest in recent years: whether machine learning-assisted algorithms can genuinely outperform classical approaches in challenging ...
Abstract: We consider a class of stochastic optimal control problems for discrete-time linear systems whose objective is the characterization of control policies that will steer the probability ...
Understanding the mechanism of how neural networks learn features from data is a fundamental problem in machine learning. Our work explicitly connects the mechanism of neural feature learning to a ...
We present two frameworks for design optimization of a multi-chamber pneumatic-driven soft actuator to optimize its mechanical performance. The design goal is to achieve maximal horizontal motion of ...
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