论文标题
在专业硬件上基于ISING的共识聚类
Ising-based Consensus Clustering on Specialized Hardware
论文作者
论文摘要
专门优化硬件（例如CMOS退火器和绝热量子计算机）的出现具有更有效地在硬件中更有效地解决硬件组合优化问题的希望。最近的工作重点是制定不同的组合优化问题，例如ISING模型，这是大量这些硬件平台使用的核心数学抽象，并在使用专用硬件解决时评估了这些模型的性能。应用程序的一个有趣领域是数据挖掘，其中组合优化问题是许多核心任务的基础。在这项工作中，我们专注于共识聚类（聚集聚合），这是一个重要的组合问题，在过去的二十年中，人们一直受到了很多关注。我们提出了两个用于共识聚类的ISING模型，并使用Fujitsu Digital Exealer（一种量子启发的CMOS退火器）对其进行评估。我们的经验评估表明，我们的方法表现优于现有技术，并且是未来研究的有希望的方向。
The emergence of specialized optimization hardware such as CMOS annealers and adiabatic quantum computers carries the promise of solving hard combinatorial optimization problems more efficiently in hardware. Recent work has focused on formulating different combinatorial optimization problems as Ising models, the core mathematical abstraction used by a large number of these hardware platforms, and evaluating the performance of these models when solved on specialized hardware. An interesting area of application is data mining, where combinatorial optimization problems underlie many core tasks. In this work, we focus on consensus clustering (clustering aggregation), an important combinatorial problem that has received much attention over the last two decades. We present two Ising models for consensus clustering and evaluate them using the Fujitsu Digital Annealer, a quantum-inspired CMOS annealer. Our empirical evaluation shows that our approach outperforms existing techniques and is a promising direction for future research.
