Are expensive hardware upgrades solving the wrong problem? Many gamers experience performance issues and immediately assume their hardware is the cause. They notice stutters, input lag, or ...

NVIDIA's GPU-accelerated cuOpt engine discovers new solutions for four MIPLIB benchmark problems, outperforming CPU solvers with 22% lower objective gaps. NVIDIA's cuOpt optimization engine has found ...

Abstract: Distributed optimization provides a framework for deriving distributed algorithms for a variety of multi-robot problems. This tutorial constitutes the first part of a two-part series on ...

Optimization problems often involve situations in which the user's goal is to minimize and/or maximize not a single objective function, but several, usually conflicting, functions simultaneously. Such ...

We walk through an optimization problem step by step, clearly explaining how to identify variables, set up the correct function, apply derivatives, and find maximum or minimum values. Each step is ...

ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...

In this talk, I will give a high-level tutorial on graphs of convex sets, with emphasis on their applications in robotics, control, and, more broadly, decision making. Mathematically, a Graph of ...

Is your feature request related to a problem? Please describe. I find it hard to translate the help given in FAQ on Optimization/AD into code that actually performs a parameter optimization. I propose ...

We present OPT-BENCH, a benchmark comprising 20 machine learning tasks and 10 NP problems, specifically designed to assess large language models’ (LLMs) ability to solve problems with large search ...

The original version of this story appeared in Quanta Magazine. For computer scientists, solving problems is a bit like mountaineering. First they must choose a problem to solve—akin to identifying a ...