This paper studies the fair influence maximization problem with efficient algorithms. In particular, given a graph G, a community structure C consisting of disjoint communities, and a budget k, the ...

Master problem-solving with a simple, powerful 3-step approach that works across all languages and challenges. Whitefish crash has Michigan fishers on the brink: ‘It makes you want to cry’ Donald ...

Like the rest of its Big Tech cadre, Google has spent lavishly on developing generative AI models. Google’s AI can clean up your text messages and summarize the web, but the company is constantly ...

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...

from cuopt.linear_programming import DataModel, Solve, SolverSettings import numpy as np from cuopt_mps_parser import ParseMps dm = ParseMps("Bug2.mps") sol = Solve ...

Shekar Natarajan is the founder and CEO of Orchestro.AI. This example is one of many that demonstrates how supply chains are complex, interconnected, interdependent systems. They follow the ...

Web3 has a memory problem. Not in the “we forgot something” sense, but in the core architectural sense. It doesn’t have a real memory layer. Blockchains today don’t look completely alien compared to ...

ABSTRACT: This paper deals with linear programming techniques and their application in optimizing lecture rooms in an institution. This linear programming formulated based on the available secondary ...

Abstract: Network utility maximization (NUM) addresses the problem of allocating resources fairly within a network and explores the ways to achieve optimal allocation in real-world networks. Although ...

Abstract: The mainlobe directivity maximization problem for shaped beams of linear and planar arrays is addressed based on the framework of alternating direction method of multipliers (ADMMs). First, ...

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