Abstract: Gradient-type distributed optimization methods have blossomed into one of the most important tools for solving a minimization learning task over a networked agent system. However, only one ...

Traditional approaches to analytical method optimization (e.g., univariate and “guess-and-check”) can be time-consuming, costly, and often fail to identify true optima within the parameter space.

College of Mechanical and Electronic Engineering, Shanghai Jianqiao University, Shanghai, China Introduction: To enhance energy management in electric vehicles (EVs), this study proposes an ...

The challenge takes place from July 11-20 in designated South Florida locations. Participants compete for prizes, including $10,000 for removing the most pythons. Pythons must be killed humanely using ...

A new algorithm helps topology optimizers skip unnecessary iterations, making optimization and design faster, more stable and more useful. PROVIDENCE, R.I. [Brown University] — With the rise of 3D ...

Supply chain forecasting is becoming an increasingly critical component of operational success. Accurate forecasting enables companies to optimize inventory levels, reduce waste, enhance customer ...

The bleeding edge: In-memory processing is a fascinating concept for a new computer architecture that can compute operations within the system's memory. While hardware accommodating this type of ...

I am here to ask a question about the QuantLib wrapper in Python. I would like to use the G2 class to have a Two-additive-factor Gaussian model and I would like to have the discount coupon of this ...

Change is the only constant in today’s rapidly evolving digital marketing landscape. Keeping up with the latest innovations isn’t just a choice – it’s a necessity for survival. Generative engine ...