Zobrazeno 1 - 10
of 6 584
pro vyhledávání: '"Tripp, P."'
Autor:
Luna, Priscilla Holguin, Burchett, Joseph N., Nagai, Daisuke, Tripp, Todd M., Tejos, Nicolas, Prochaska, J. Xavier
The intracluster medium (ICM) in the far outskirts (r $>$ 2-3 R$_{200}$) of galaxy clusters interfaces with the intergalactic medium (IGM) and is theorized to comprise diffuse, multiphase gas. This medium may hold vital clues to clusters' thermodynam
Externí odkaz:
http://arxiv.org/abs/2411.13551
We extend the recently developed quantum van der Waals quarkyonic matter to non-zero isospin asymmetries by utilizing the two-component van der Waals equation with a generalized excluded volume prescription. The isospin dependence of van der Waals in
Externí odkaz:
http://arxiv.org/abs/2411.11996
Recent studies have shown that many nonconvex machine learning problems meet a so-called generalized-smooth condition that extends beyond traditional smooth nonconvex optimization. However, the existing algorithms designed for generalized-smooth nonc
Externí odkaz:
http://arxiv.org/abs/2410.14054
Autor:
Fromer, Jenna, Wang, Runzhong, Manjrekar, Mrunali, Tripp, Austin, Hernández-Lobato, José Miguel, Coley, Connor W.
Batched Bayesian optimization (BO) can accelerate molecular design by efficiently identifying top-performing compounds from a large chemical library. Existing acquisition strategies for batch design in BO aim to balance exploration and exploitation.
Externí odkaz:
http://arxiv.org/abs/2410.06333
Making successful use of cloud computing for deploying scalable web applications requires nuanced approaches to both system design and deployment methodology, involving reasoning about the elasticity, cost, and security models of cloud services. Stud
Externí odkaz:
http://arxiv.org/abs/2410.01032
Bayesian optimization (BO) is a principled approach to molecular design tasks. In this paper we explain three pitfalls of BO which can cause poor empirical performance: an incorrect prior width, over-smoothing, and inadequate acquisition function max
Externí odkaz:
http://arxiv.org/abs/2406.07709
Autor:
Hossain, Soneya Binta, Jiang, Nan, Zhou, Qiang, Li, Xiaopeng, Chiang, Wen-Hao, Lyu, Yingjun, Nguyen, Hoan, Tripp, Omer
Large language models (LLMs) have shown impressive effectiveness in various software engineering tasks, including automated program repair (APR). In this study, we take a deep dive into automated bug fixing utilizing LLMs. In contrast to many deep le
Externí odkaz:
http://arxiv.org/abs/2404.11595
This paper introduces a nonconvex approach for sparse signal recovery, proposing a novel model termed the $\tau_2$-model, which utilizes the squared $\ell_1/\ell_2$ norms for this purpose. Our model offers an advancement over the $\ell_0$ norm, which
Externí odkaz:
http://arxiv.org/abs/2404.00764
Autor:
Tripp, Charles Edison, Perr-Sauer, Jordan, Gafur, Jamil, Nag, Amabarish, Purkayastha, Avi, Zisman, Sagi, Bensen, Erik A.
Addressing the so-called ``Red-AI'' trend of rising energy consumption by large-scale neural networks, this study investigates the actual energy consumption, as measured by node-level watt-meters, of training various fully connected neural network ar
Externí odkaz:
http://arxiv.org/abs/2403.08151
Autor:
Siadati, Hossein, Jafarikhah, Sima, Sahin, Elif, Hernandez, Terrence Brent, Tripp, Elijah Lorenzo, Khryashchev, Denis, Kharraz, Amin
The Software Supply Chain (SSC) has captured considerable attention from attackers seeking to infiltrate systems and undermine organizations. There is evidence indicating that adversaries utilize Social Engineering (SocE) techniques specifically aime
Externí odkaz:
http://arxiv.org/abs/2402.18401