Some problems are just too complex to solve exactly in a reasonable amount of time. That's where approximation algorithms come in. They don't get the perfect answer, but they give an answer that's ...
Abstract: In this paper, we propose the Priority Facility Location Problem with Outliers (PFLPO), which is a generalization of both the Facility Location Problem with Outliers (FLPO) and Priority ...
The optimal operation model of AC/DC distribution network with energy router (ER) is essentially a nonconvex nonlinear programming (NLP) problem. In order to improve the feasibility of solving the ...
Mark Jerrum, Alistair Sinclair (UC Berkeley) and Eric Vigoda (Georgia Tech) received the Association for Computing Machinery (ACM) Test of Time Award at a virtual ceremony on Wednesday 23 June at the ...
Betweenness centrality is one of the key measures of the node importance in a network. However, it is computationally intractable to calculate the exact betweenness centrality of nodes in large-scale ...
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: This paper presents a new approach to analog-to-digital converter (ADC) for low to medium-activity signals. We integrate the concept of reinforcement learning into the successive ...
Algorithms are everywhere, even when we do not notice them. They help us search the web, navigate roads, and discover new content online. Understanding how algorithms work is one of the simplest ways ...
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