Zobrazeno 1 - 10
of 65 296
pro vyhledávání: '"A. Murali"'
Autor:
A. Murali, K. Muthunagai
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-17 (2024)
Abstract This paper introduces a novel fast iterative process designed for approximating fixed points of contraction and weak contraction mappings. The study presents strong convergence results for this newly proposed iterative process, and proving i
Externí odkaz:
https://doaj.org/article/d816d0a61f2e4e40bdd545e8397712b4
Autor:
A. Murali, K. Muthunagai
Publikováno v:
Journal of Nigerian Society of Physical Sciences, Vol 6, Iss 2 (2024)
Recent studies have highlighted fixed point theorems in the context of bicomplex valued metric spaces, utilizing rational type contractions with coefficients defined by two-variable control functions. In our research, we extend these findings by prop
Externí odkaz:
https://doaj.org/article/4d7db0d0e158491485e0edb61e24239d
Autor:
R. Undamatla, O. G. Fagunloye, J. Chen, L. R. Edmunds, A. Murali, A. Mills, B. Xie, M. M. Pangburn, I. Sipula, G. Gibson, C. St. Croix, M. J. Jurczak
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-13 (2023)
Abstract Nonalcoholic fatty liver disease (NAFLD) encompasses a spectrum of pathologies that includes steatosis, steatohepatitis (NASH) and fibrosis and is strongly associated with insulin resistance and type 2 diabetes. Changes in mitochondrial func
Externí odkaz:
https://doaj.org/article/aa7fe506c5da4b44ab0be9759318a6ae
Autor:
Chitty-Venkata, Krishna Teja, Raskar, Siddhisanket, Kale, Bharat, Ferdaus, Farah, Tanikanti, Aditya, Raffenetti, Ken, Taylor, Valerie, Emani, Murali, Vishwanath, Venkatram
Large Language Models (LLMs) have propelled groundbreaking advancements across several domains and are commonly used for text generation applications. However, the computational demands of these complex models pose significant challenges, requiring e
Externí odkaz:
http://arxiv.org/abs/2411.00136
Autor:
Zhang, Chaoyun, Yao, Randolph, Qin, Si, Li, Ze, Agrawal, Shekhar, Mishra, Binit R., Tran, Tri, Ma, Minghua, Lin, Qingwei, Chintalapati, Murali, Zhang, Dongmei
The presence of unhealthy nodes in cloud infrastructure signals the potential failure of machines, which can significantly impact the availability and reliability of cloud services, resulting in negative customer experiences. Effectively addressing u
Externí odkaz:
http://arxiv.org/abs/2410.17709
Autor:
Huang, Huang, Sundaralingam, Balakumar, Mousavian, Arsalan, Murali, Adithyavairavan, Goldberg, Ken, Fox, Dieter
Running optimization across many parallel seeds leveraging GPU compute have relaxed the need for a good initialization, but this can fail if the problem is highly non-convex as all seeds could get stuck in local minima. One such setting is collision-
Externí odkaz:
http://arxiv.org/abs/2410.16727
As cloud-based ML expands, ensuring data security during training and inference is critical. GPU-based Trusted Execution Environments (TEEs) offer secure, high-performance solutions, with CPU TEEs managing data movement and GPU TEEs handling authenti
Externí odkaz:
http://arxiv.org/abs/2410.15240
In this work, we consider the problem of learning end to end perception to control for ground vehicles solely from aerial imagery. Photogrammetric simulators allow the synthesis of novel views through the transformation of pre-generated assets into n
Externí odkaz:
http://arxiv.org/abs/2410.14177
When annotators disagree, predicting the labels given by individual annotators can capture nuances overlooked by traditional label aggregation. We introduce three approaches to predicting individual annotator ratings on the toxicity of text by incorp
Externí odkaz:
http://arxiv.org/abs/2410.12217
Autor:
Abreu, Rui, Murali, Vijayaraghavan, Rigby, Peter C, Maddila, Chandra, Sun, Weiyan, Ge, Jun, Chinniah, Kaavya, Mockus, Audris, Mehta, Megh, Nagappan, Nachiappan
Release engineering has traditionally focused on continuously delivering features and bug fixes to users, but at a certain scale, it becomes impossible for a release engineering team to determine what should be released. At Meta's scale, the responsi
Externí odkaz:
http://arxiv.org/abs/2410.06351