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 ...
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 ...
Companies like OpenAI and China’s DeepSeek offer chatbots designed to take their time with an answer. Here’s how they work. By Cade Metz and Dylan Freedman Cade Metz reported from San Francisco and ...
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 ...
OpenAI researchers have admitted that even the most advanced AI models still are no match for human coders — even though CEO Sam Altman insists they will be able to beat “low-level” software engineers ...
ABSTRACT: This study proposes a novel approach to optimizing individual work schedules for book digitization using mixed-integer programming (MIP). By leveraging the power of MIP solvers, we aimed to ...
In this paper we compare track data association purity, accuracy, and timing on a simple, idealized model tracking problem for two data association methods: Global Nearest Neighbor (GNN) and Linear ...
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