Results 21 to 30 of about 1,164,839 (255)
SPlit: An Optimal Method for Data Splitting [PDF]
Technometrics, 2020 In this article, we propose an optimal method referred to as SPlit for splitting a dataset into training and testing sets. SPlit is based on the method of support points (SP), which was initially developed for finding the optimal representative points of
V. R. Joseph, Akhil Vakayil
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Chiral Split Magnon in Altermagnetic MnTe. [PDF]
Physical Review LettersAltermagnetism is a newly recognized magnetic class named after the alternating spin polarizations in both real and reciprocal spaces. Like the spin splitting of electronic bands, the magnon bands in altermagnets are predicted to exhibit alternating ...
Zheyuan Liu +4 more
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Formalized Mathematics, 2021 Summary. In this article we further develop field theory in Mizar [1], [2]: we prove existence and uniqueness of splitting fields. We define the splitting field of a polynomial p ∈ F [X] as the smallest field extension of F, in which p splits into linear factors.
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Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training? [PDF]
ACM Asia Conference on Computer and Communications Security, 2020 A new collaborative learning, called split learning, was recently introduced, aiming to protect user data privacy without revealing raw input data to a server.
Sharif Abuadbba +7 more
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Proceedings of the American Mathematical Society, 1991 Let B n {B_n} be the group of braids on n n strings with standard generators σ 1 , … , σ n − 1
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The Split-Apply-Combine Strategy for Data Analysis
, 2011 Many data analysis problems involve the application of a split-apply-combine strategy, where you break up a big problem into manageable pieces, operate on each piece independently and then put all the pieces back together.
H. Wickham
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Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction [PDF]
Computer Vision and Pattern Recognition, 2016 We propose split-brain autoencoders, a straightforward modification of the traditional autoencoder architecture, for unsupervised representation learning. The method adds a split to the network, resulting in two disjoint sub-networks. Each sub-network is
Richard Zhang +2 more
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SISVAR: A COMPUTER ANALYSIS SYSTEM TO FIXED EFFECTS SPLIT PLOT TYPE DESIGNS
, 2019 This paper presents a special capability of Sisvar to deal with fixed effect models with several restriction in the randomization procedure. These restrictions lead to models with fixed treatment effects, but with several random errors.
D. F. Ferreira
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Split-TurboID enables contact-dependent proximity labeling in cells
Proceedings of the National Academy of Sciences of the United States of America, 2020 Significance Most of the thousands of proteins that comprise a human cell have specific subcellular localization patterns essential for their function. “Proximity labeling” (PL) is a method for mapping the localization of endogenous cellular proteins on ...
K. Cho +10 more
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Face Hallucination via Split-Attention in Split-Attention Network [PDF]
ACM Multimedia, 2020 Recently, convolutional neural networks (CNNs) have been widely employed to promote the face hallucination due to the ability to predict high-frequency details from a large number of samples.
T. Lu +6 more
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