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pro vyhledávání: '"Lieberman AN"'
Although binary classification is a well-studied problem, training reliable classifiers under severe class imbalance remains a challenge. Recent techniques mitigate the ill effects of imbalance on training by modifying the loss functions or optimizat
Externí odkaz:
http://arxiv.org/abs/2410.03588
Autor:
Colon-Hernandez, Pedro, Liu, Nanxi, Joe, Chelsea, Chin, Peter, Yin, Claire, Lieberman, Henry, Xin, Yida, Breazeal, Cynthia
Generating commonsense assertions within a given story context remains a difficult task for modern language models. Previous research has addressed this problem by aligning commonsense inferences with stories and training language generation models a
Externí odkaz:
http://arxiv.org/abs/2410.02202
Autor:
Gao, Yifan, Mughal, Zakariyya, Jaramillo-Villegas, Jose A., Corradi, Marie, Borrel, Alexandre, Lieberman, Ben, Sharif, Suliman, Shaffer, John, Fecho, Karamarie, Chatrath, Ajay, Maertens, Alexandra, Teunis, Marc A. T., Kleinstreuer, Nicole, Hartung, Thomas, Luechtefeld, Thomas
Researchers in biomedical research, public health, and the life sciences often spend weeks or months discovering, accessing, curating, and integrating data from disparate sources, significantly delaying the onset of actual analysis and innovation. In
Externí odkaz:
http://arxiv.org/abs/2408.17320
Modern 3D printers allow for the accurate placing of microscopic material voxels, to form complex three-dimensional structures. The advancing capabilities in multi-material printing, coupled with the discovery of printable responsive materials, pave
Externí odkaz:
http://arxiv.org/abs/2406.12113
Autor:
Lieberman, Benjamin, Dahbi, Salah-Eddine, Crivellin, Andreas, Stevenson, Finn, Tripathi, Nidhi, Kumar, Mukesh, Mellado, Bruce
Publikováno v:
SciPost Phys. Core 7, 073 (2024)
To mitigate the model dependencies of searches for new narrow resonances at the Large Hadron Collider (LHC), semi-supervised Neural Networks (NNs) can be used. Unlike fully supervised classifiers these models introduce an additional look-elsewhere ef
Externí odkaz:
http://arxiv.org/abs/2404.07822
Autor:
Jeffries, Jack, Lieberman, David
Bernstein's inequality is a central result in the theory of $D$-modules on smooth varieties. While Bernstein's inequality fails for rings of differential operators on general singularities, recent work of \`{A}lvarez Montaner, Hern\'andez, Jeffries,
Externí odkaz:
http://arxiv.org/abs/2403.13146
Autor:
Hong, Junyuan, Duan, Jinhao, Zhang, Chenhui, Li, Zhangheng, Xie, Chulin, Lieberman, Kelsey, Diffenderfer, James, Bartoldson, Brian, Jaiswal, Ajay, Xu, Kaidi, Kailkhura, Bhavya, Hendrycks, Dan, Song, Dawn, Wang, Zhangyang, Li, Bo
Compressing high-capability Large Language Models (LLMs) has emerged as a favored strategy for resource-efficient inferences. While state-of-the-art (SoTA) compression methods boast impressive advancements in preserving benign task performance, the p
Externí odkaz:
http://arxiv.org/abs/2403.15447
Autor:
Blohm, Gunnar, Peters, Benjamin, Haefner, Ralf, Isik, Leyla, Kriegeskorte, Nikolaus, Lieberman, Jennifer S., Ponce, Carlos R., Roig, Gemma, Peters, Megan A. K.
Generative adversarial collaborations (GACs) are a form of formal teamwork between groups of scientists with diverging views. The goal of GACs is to identify and ultimately resolve the most important challenges, controversies, and exciting theoretica
Externí odkaz:
http://arxiv.org/abs/2402.12604
Although binary classification is a well-studied problem in computer vision, training reliable classifiers under severe class imbalance remains a challenging problem. Recent work has proposed techniques that mitigate the effects of training under imb
Externí odkaz:
http://arxiv.org/abs/2402.05400
*This paper is from 2018* In this paper, we try to classify moduli spaces of arrangements of $12$ lines with sextic points. We show that moduli spaces of arrangements of $12$ lines with sextic points can consist of more than two connected components.
Externí odkaz:
http://arxiv.org/abs/2401.00821