ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...
This repository contains experiment that implements Bayesian Optimization (BO) techniques for Conditional Value-at-Risk (CVaR)-based portfolio optimization, inspired by the research paper "Bayesian ...
In the fast-evolving field of electronic systems design, engineers are under increasing pressure to deliver innovative, high-performance products within ever ...
Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan Graduate School of Science and Technology, Nara Institute of ...
INNOptimizer is using latest Bayesian Optimization algorithms and a broad set of analytical tools to guide optimizations with minimum experimentation needed. Don't waste time and money with poor ...
Artificial intelligence (AI) is playing a huge role in heat rate optimization. In some cases, AI-driven models have analyzed operational data to recommend control settings that reduce heat rates by ...
This workshop on Engineering Design Optimization using MATLAB® and Python™ addresses the shape optimization of mechanical components for strength. Python ...
Abstract: Controller tuning and parameter optimization are crucial in system design to improve closed-loop system performance. Bayesian optimization has been established as an efficient model-free ...
Abstract: As an important technology in high-speed systems, equalizer (EQ) is used to mitigate inter-symbol interference (ISI) caused by inconsistent attenuation of high and low frequencies. The ...
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