The quality of fragments allocation is key for improving performance of join query in distributed database. Current strategies concentrate on using heuristic rules to allocate fragments to corresponding location
Method: greedy Divides up the data greedily given a specified group size. E.g. group sizes: 10, 10, 10, 10, 10, 7 Specify number of groups Method: n_dist (Default) Divides the data into a specified number of groups and distributes excess data points across groups. E.g. group sizes...
Unfortunately, the discernibility matrix-based reduction method is commonly computationally expensive, and it is quite intolerable for dealing with large-scale and high-dimensional data sets. Therefore, in this section, the relative discernibility and the corresponding properties are introduced first. Next...
Greedy Sampler and Dumb Learner (GDumb): gdumb. Hindsight Anchor Learning (HAL): hal. Image-aware Decoder Enhanced à la Flamingo with Interleaved Cross-attentionS (IDEFICS): idefics (static method with no learning). Incremental Classifier and Representation Learning (iCaRL): icarl. Joint training...
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Community structure detection is a clustering method based in graph theory33, that we used to classify the participants into groups based on five characteristics of their sleep quality. These characteristics were sleep duration, sleep onset latency, sleep efficiency, sleep disturbances, and subjective ...
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Scientific Reports | (2021) 11:7735 | https://doi.org/10.1038/s41598-021-87318-4 7 Vol.:(0123456789) www.nature.com/scientificreports/ Cluster analysis. Community structure detection is a clustering method based in graph theory33, that we used to classify the participants into groups...
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Furthermore, except for the substituted fusion method, all other configurations of our framework remain consistent across experiments to ensure a fair comparison. Table 2. Dominated uni-modal models consistently outperform the multi-modal models (concatenated fusion) for all three different tasks. In-...