Zobrazeno 1 - 10
of 6 759
pro vyhledávání: '"Bornstein, P."'
Autor:
Bornstein, Marco, Che, Zora, Julapalli, Suhas, Mohamed, Abdirisak, Bedi, Amrit Singh, Huang, Furong
In an era of "moving fast and breaking things", regulators have moved slowly to pick up the safety, bias, and legal pieces left in the wake of broken Artificial Intelligence (AI) deployment. Since AI models, such as large language models, are able to
Externí odkaz:
http://arxiv.org/abs/2410.01871
Autor:
Baumel, Tal, Manoel, Andre, Jones, Daniel, Su, Shize, Inan, Huseyin, Aaron, Bornstein, Sim, Robert
In the field of machine learning, domain-specific annotated data is an invaluable resource for training effective models. However, in the medical domain, this data often includes Personal Health Information (PHI), raising significant privacy concerns
Externí odkaz:
http://arxiv.org/abs/2409.07809
We propose a flexible Bayesian approach for sparse Gaussian graphical modeling of multivariate time series. We account for temporal correlation in the data by assuming that observations are characterized by an underlying and unobserved hidden discret
Externí odkaz:
http://arxiv.org/abs/2406.03385
Autor:
Lawson, Peter R., Kizovski, Tanya V., Tice, Michael M., Clark III, Benton C., VanBommel, Scott J., Thompson, David R., Wade, Lawrence A., Denise, Robert W., Heirwegh, Christopher M., Elam, W. Timothy, Schmidt, Mariek E., Liu, Yang, Allwood, Abigail C., Gilbert, Martin S., Bornstein, Benjamin J.
Planetary rovers can use onboard data analysis to adapt their measurement plan on the fly, improving the science value of data collected between commands from Earth. This paper describes the implementation of an adaptive sampling algorithm used by PI
Externí odkaz:
http://arxiv.org/abs/2405.14471
Standard federated learning (FL) approaches are vulnerable to the free-rider dilemma: participating agents can contribute little to nothing yet receive a well-trained aggregated model. While prior mechanisms attempt to solve the free-rider dilemma, n
Externí odkaz:
http://arxiv.org/abs/2405.13879
Edge device participation in federating learning (FL) is typically studied through the lens of device-server communication (e.g., device dropout) and assumes an undying desire from edge devices to participate in FL. As a result, current FL frameworks
Externí odkaz:
http://arxiv.org/abs/2310.13681
Autor:
Evan Fair, Jacob Bornstein, Timothy Lyons, Phillip Sgobba, Alana Hayes, Megan Rourke, Isaac Macwan, Naser Haghbin
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Replicating the architecture of extracellular matrices (ECM) is crucial in tissue engineering to support tissues’ natural structure and functionality. The ECM’s structure plays a significant role in directing cell alignment. Electrospinn
Externí odkaz:
https://doaj.org/article/531c328a7e094dc89abce3d82bd0eb22
Locality-sensitive hashing (LSH) based frameworks have been used efficiently to select weight vectors in a dense hidden layer with high cosine similarity to an input, enabling dynamic pruning. While this type of scheme has been shown to improve compu
Externí odkaz:
http://arxiv.org/abs/2306.02563
Autor:
Lüer, Larry, Peters, Marius, Bornstein, Dan, Corre, Vincent M. Le, Forberich, Karen, Guldi, Dirk, Brabec, Christoph J.
In single-junction photovoltaic (PV) devices, the maximum achievable power conversion efficiency (PCE) is mainly limited by thermalization and transmission losses, because polychromatic solar irradiation cannot be matched to a single bandgap. Several
Externí odkaz:
http://arxiv.org/abs/2305.11815
Autor:
Bornstein, Thomas, Lange, Dietrich, Münchmeyer, Jannes, Woollam, Jack, Rietbrock, Andreas, Barcheck, Grace, Grevemeyer, Ingo, Tilmann, Frederik
Detecting phase arrivals and pinpointing the arrival times of seismic phases in seismograms is crucial for many seismological analysis workflows. For land station data machine learning methods have already found widespread adoption. However, deep lea
Externí odkaz:
http://arxiv.org/abs/2304.06635