Zobrazeno 1 - 10
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pro vyhledávání: '"P, Bornstein"'
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:
Samantha L. Hahn, Caroline Bornstein, C. Blair Burnette, Katie A. Loth, Dianne Neumark-Sztainer
Publikováno v:
Journal of Eating Disorders, Vol 12, Iss 1, Pp 1-11 (2024)
Abstract Background Weight-related self-monitoring (WRSM) apps are used by millions, but the effects of their use remain unclear. This study examined longitudinal relationships between WRSM and disordered eating among a population-based sample of eme
Externí odkaz:
https://doaj.org/article/4d8f9f868a5641159d0b9b4e60926823
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
Autor:
Kasha Bornstein, Elizabeth LaRosa, Kelsey Byrd, Dan Laney, Hector Ferral, Heather Murphy-Lavoie
Publikováno v:
Clinical Practice and Cases in Emergency Medicine, Vol 8, Iss 2, Pp 163-167 (2024)
Introduction: Phlegmasia cerulea dolens (PCD) is an uncommon, potentially life-threatening complication of acute deep venous thromboses that requires a timely diagnosis. The name of the condition, the visual diagnostic criteria, and the preponderance
Externí odkaz:
https://doaj.org/article/bae5be3d140e4af59af10541ae3130d4
Large-scale non-convex optimization problems are expensive to solve due to computational and memory costs. To reduce the costs, first-order (computationally efficient) and asynchronous-parallel (memory efficient) algorithms are necessary to minimize
Externí odkaz:
http://arxiv.org/abs/2211.09908