Results 21 to 30 of about 1,216,959 (343)
Fast-Convergent Federated Learning with Adaptive Weighting [PDF]
ICC 2021 - IEEE International Conference on Communications, 2020 Federated learning (FL) enables resource-constrained edge nodes to collaboratively learn a global model under the orchestration of a central server while keeping privacy-sensitive data locally.
Hongda Wu, Ping Wang
semanticscholar +1 more source
Learning Fast Sample Re-weighting Without Reward Data [PDF]
IEEE International Conference on Computer Vision, 2021 Training sample re-weighting is an effective approach for tackling data biases such as imbalanced and corrupted labels. Recent methods develop learning-based algorithms to learn sample re-weighting strategies jointly with model training based on the ...
Zizhao Zhang, Tomas Pfister
semanticscholar +1 more source
Body weight relationships in early marriage. Weight relevance, weight comparisons, and weight talk [PDF]
Appetite, 2011 This investigation uncovered processes underlying the dynamics of body weight and body image among individuals involved in nascent heterosexual marital relationships in Upstate New York. In-depth, semi-structured qualitative interviews conducted with 34 informants, 20 women and 14 men, just prior to marriage and again one year later were used to ...
Caron F, Bove, Jeffery, Sobal
openaire +2 more sources
Axioms, 2022 Analysis of power converter performance has tended to be engineering-oriented, focusing mainly on voltage stability, output power and efficiency improvement. However, there has been little discussion about the weight relations between these factors.
Shih-Kuen Changchien, Kun-Li Wen
doaj +1 more source
Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation
bioRxiv, 2016 Long-read single-molecule sequencing has revolutionized de novo genome assembly and enabled the automated reconstruction of reference-quality genomes. However, given the relatively high error rates of such technologies, efficient and accurate assembly of
S. Koren +5 more
semanticscholar +1 more source
Density-based weighting for imbalanced regression
Machine-mediated learning, 2021 In many real world settings, imbalanced data impedes model performance of learning algorithms, like neural networks, mostly for rare cases. This is especially problematic for tasks focusing on these rare occurrences.
M. Steininger +4 more
semanticscholar +1 more source
Demographic Research, 2016 Background: The Generations and Gender Survey (GGS) was developed to stimulate the study of a broad range of topics of relevance to population scientists. So far, at least one wave of the GGS has been conducted in 19 countries.
Tineke Fokkema +4 more
doaj +1 more source
Feature Weighting and Boosting for Few-Shot Segmentation [PDF]
IEEE International Conference on Computer Vision, 2019 This paper is about few-shot segmentation of foreground objects in images. We train a CNN on small subsets of training images, each mimicking the few-shot setting.
Khoi Duc Minh Nguyen, S. Todorovic
semanticscholar +1 more source
International Journal of Population Data Science, 2022 Objective The prospective cohort study design is ideal for examining diseases of public health importance. A main source of potential bias for longitudinal studies is attrition. In this study, we compare the performance of two models developed to predict
Tona Pitt +3 more
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Spatial Weighting Matrix Selection in Spatial Lag Econometric Model [PDF]
, 2013 This paper investigates the choice of spatial weighting matrix in a spatial lag model framework. In the empirical literature the choice of spatial weighting matrix has been characterized by a great deal of arbitrariness.
Kostov, Phillip
core +1 more source