Most of you have used a navigation app like Google Maps for your travels at some point. These apps rely on algorithms that ...

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

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

Recent advancements in quantum computing and quantum-inspired algorithms have sparked renewed interest in binary optimization. These hardware and software innovations promise to revolutionize solution ...

In recent years, neural networks have once again triggered an increased interest among researchers in the machine learning community. So-called deep neural networks model functions using a composition ...

\[ \gdef\bias{\mathrm{bias}} \gdef\deg{\mathrm{deg}} \gdef\indeg{\mathrm{indeg}} \gdef\outdeg{\mathrm{outdeg}} \gdef\Snap{\mathrm{Snap}} \gdef\RSnap{\mathrm{RefSnap ...

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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 ...