Data is often referred to as the new oil of the digital economy, representing a highly valuable and untapped asset. To fully realize the potential of spatial data, various spatial data marketplace ...

Over the past decades, computer scientists have introduced numerous artificial intelligence (AI) systems designed to emulate ...

Most of you have used a navigation app like Google Maps for your travels at some point. These apps rely on algorithms that compute shortest paths through vast networks. Now imagine scaling that task ...

Metric spaces form the backbone of modern computational geometry by providing a rigorous framework for measuring distances within abstract sets, while geometric approximation algorithms yield ...

Abstract: Noncommutative constraint satisfaction problems (CSPs) are higher-dimensional operator extensions of classical CSPs. Their approximability remains largely unexplored. A notable example of a ...

Robotic surfaces consisting of many actuators can change shape to perform tasks, such as object transportation and sorting. Increasing the number of actuators can enhance the robot’s capacity, but ...

Abstract: In applied and numerical algebraic geometry, many problems are reduced to computing an approximation to a real algebraic curve. In order to elevate the results of such a computation to the ...

We propose the Trust Region Preference Approximation (TRPA) algorithm ⚙️, which integrates rule-based optimization with preference-based optimization for LLM reasoning tasks 🤖🧠. As a ...

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ABSTRACT: The purpose of reoptimization using approximation methods—application of knowledge about the solution of the initial instance I, provided to achieve a better quality of approximation ...