Zobrazeno 1 - 10
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pro vyhledávání: '"Were, Phoebe"'
Autor:
Sharpnack, James, Hao, Kevin, Mulcaire, Phoebe, Bicknell, Klinton, LaFlair, Geoff, Yancey, Kevin, von Davier, Alina A.
In this paper, we present a complete framework for quickly calibrating and administering a robust large-scale computerized adaptive test (CAT) with a small number of responses. Calibration - learning item parameters in a test - is done using AutoIRT,
Externí odkaz:
http://arxiv.org/abs/2410.21033
Multimedia streaming accounts for the majority of traffic in today's internet. Mechanisms like adaptive bitrate streaming control the bitrate of a stream based on the estimated bandwidth, ideally resulting in smooth playback and a good Quality of Exp
Externí odkaz:
http://arxiv.org/abs/2410.21029
Autor:
Ferreira, Fabio S., Ashburner, John, Bouzigues, Arabella, Suksasilp, Chatrin, Russell, Lucy L., Foster, Phoebe H., Ferry-Bolder, Eve, van Swieten, John C., Jiskoot, Lize C., Seelaar, Harro, Sanchez-Valle, Raquel, Laforce, Robert, Graff, Caroline, Galimberti, Daniela, Vandenberghe, Rik, de Mendonca, Alexandre, Tiraboschi, Pietro, Santana, Isabel, Gerhard, Alexander, Levin, Johannes, Sorbi, Sandro, Otto, Markus, Pasquier, Florence, Ducharme, Simon, Butler, Chris R., Ber, Isabelle Le, Finger, Elizabeth, Tartaglia, Maria C., Masellis, Mario, Rowe, James B., Synofzik, Matthis, Moreno, Fermin, Borroni, Barbara, Kaski, Samuel, Rohrer, Jonathan D., Mourao-Miranda, Janaina
In this study, we propose a novel approach to uncover subgroup-specific and subgroup-common latent factors addressing the challenges posed by the heterogeneity of neurological and mental disorders, which hinder disease understanding, treatment develo
Externí odkaz:
http://arxiv.org/abs/2410.07890
Autor:
Aifer, Maxwell, Duffield, Samuel, Donatella, Kaelan, Melanson, Denis, Klett, Phoebe, Belateche, Zach, Crooks, Gavin, Martinez, Antonio J., Coles, Patrick J.
A fully Bayesian treatment of complicated predictive models (such as deep neural networks) would enable rigorous uncertainty quantification and the automation of higher-level tasks including model selection. However, the intractability of sampling Ba
Externí odkaz:
http://arxiv.org/abs/2410.01793
The independence polynomial of a graph $G$ evaluated at $-1$, denoted here as $I(G;-1)$, has arisen in a variety of different areas of mathematics and theoretical physics as an object of interest. Engstr\"om used discrete Morse theory to prove that $
Externí odkaz:
http://arxiv.org/abs/2409.14576
Affect and cognitive load influence many user behaviors. In this paper, we propose Motion as Emotion, a novel method that utilizes fine differences in hand motion to recognise affect and cognitive load in virtual reality (VR). We conducted a study wi
Externí odkaz:
http://arxiv.org/abs/2409.12921
Autor:
Bacheva, Vesna, Madison, Imani, Baldwin, Mathew, Beilstein, Mark, Call, Douglas F., Deaver, Jessica A., Efimenko, Kirill, Genzer, Jan, Grieger, Khara, Gu, April Z., Ilman, Mehmet Mert, Liu, Jen, Li, Sijin, Mayer, Brooke K., Mishra, Anand Kumar, Nino, Juan Claudio, Rubambiza, Gloire, Sengers, Phoebe, Shepherd, Robert, Woodson, Jesse, Weatherspoon, Hakim, Frank, Margaret, Jones, Jacob, Sozzani, Rosangela, Stroock, Abraham
Feeding the growing human population sustainably amidst climate change is one of the most important challenges in the 21st century. Current practices often lead to the overuse of agronomic inputs, such as synthetic fertilizers and water, resulting in
Externí odkaz:
http://arxiv.org/abs/2409.12337
Emotions, shaped by past experiences, significantly influence decision-making and goal pursuit. Traditional cognitive-behavioral techniques for personal development rely on mental imagery to envision ideal selves, but may be less effective for indivi
Externí odkaz:
http://arxiv.org/abs/2409.11531
Autor:
Kress-Gazit, Hadas, Hashimoto, Kunimatsu, Kuppuswamy, Naveen, Shah, Paarth, Horgan, Phoebe, Richardson, Gordon, Feng, Siyuan, Burchfiel, Benjamin
The robot learning community has made great strides in recent years, proposing new architectures and showcasing impressive new capabilities; however, the dominant metric used in the literature, especially for physical experiments, is "success rate",
Externí odkaz:
http://arxiv.org/abs/2409.09491
Item response theory (IRT) is a class of interpretable factor models that are widely used in computerized adaptive tests (CATs), such as language proficiency tests. Traditionally, these are fit using parametric mixed effects models on the probability
Externí odkaz:
http://arxiv.org/abs/2409.08823