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AI Blogs
Fairlearn: Assessing and Improving Fairness of AI Systems Hilde Weerts, Miroslav Dudík, Richard Edgar, Adrin Jalali, Roman Lutz, Michael Madaio; 24(257):1−8, 2023. Abstract Fairlearn is a project aimed at assisting practitioners in evaluating and enhancing the fairness of artificial intelligence…
arXivLabs is a platform that enables collaborators to develop and share new features for arXiv directly on our website. Both individuals and organizations that work with arXivLabs have fully embraced and accepted our values of openness, community, excellence, and user…
Approximation Bounds for Hierarchical Clustering: Average Linkage, Bisecting K-means, and Local Search Benjamin Moseley, Joshua R. Wang; 24(1):1−36, 2023. Abstract This paper aims to provide an analytical framework for understanding hierarchical clustering, a widely used data analysis method. By establishing…
arXivLabs is a platform that enables collaborators to create and share new features for arXiv directly on our website. Both individuals and organizations that work with arXivLabs share our core values of openness, community, excellence, and user data privacy. We…
Examining the Environmental Impact of Federated Learning Xinchi Qiu, Titouan Parcollet, Javier Fernandez-Marques, Pedro P. B. Gusmao, Yan Gao, Daniel J. Beutel, Taner Topal, Akhil Mathur, Nicholas D. Lane; 24(129):1−23, 2023. Abstract Although deep learning-based technologies have shown impressive results,…
[Submitted on 29 Aug 2023] Click here to download a PDF of the paper titled “Modified Lagrangian Formulation of Gear Tooth Crack Analysis using Combined Approach of Variable Mode Decomposition (VMD) and Time Synchronous Averaging (TSA)” by Subrata Mukherjee and…
Bayesian Spiked Laplacian Graphs Authors: Leo L Duan, George Michailidis, Mingzhou Ding; Volume 24(3):1−35, 2023. Abstract In the field of network analysis, it is common to encounter a collection of graphs that exhibit heterogeneity. For instance, there is an increasing…
Developing a realistic generative model for order flow in financial markets is a complex problem with various potential applications for market participants. In this study, we propose an innovative autoregressive generative model that can produce tokenized limit order book (LOB)…
Combinatorial Optimization and Reasoning with Graph Neural Networks Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic; 24(130):1−61, 2023. Abstract Combinatorial optimization, a well-established field in operations research and computer science, has traditionally focused on solving…
The content discusses the potential use of carbon fiber composite as a replacement for metal-based battery enclosures in electric vehicles (E.V.s). The advantages of carbon fiber, such as its strength-to-weight ratio and corrosion resistance, make it a suitable candidate. However,…
