normalization   1003

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Methods of Comparison, Compared / Observable
Discover insights faster and communicate more effectively with interactive notebooks for data analysis, visualization, and exploration.
data-viz  data-science  normalization  d3js  maps  scale 
6 days ago by pmigdal
Database Normalization and Table Structures - Microsoft Access / VBA
Database Normalization and Table Structures. Get Microsoft Access / VBA help and support on Bytes.
database  normalization 
4 weeks ago by ritzlea
UAX #15: Unicode Normalization Forms
aracters: Normalization Form C and Normalization Form KC. The difference between these depends on whether the resulting text is to be a canonical equivalent to the original unnormalized text or a compatibility equivalent to the original unnormalized text. (In NFKC and NFKD, a K is used to stand for compatibility to avoid confusion with the C standing for composition.) Bot
unicode  normalization 
7 weeks ago by arsshams
CSS Tools: Reset CSS
Seemingly this has been the most highly regarded or popular css normalization around.
Or try
css  Normalization  WebDesign 
7 weeks ago by lost_in_space
Saudi Crown Prince: Palestinians should take what the U.S. offers - Axios
The bottom line of the crown prince's criticism: Palestinian leadership needs to finally take the proposals it gets from the U.S. or stop complaining.
Saudi-Arabia  Israel  Normalization  Iran  Peace_Process  Palestinian_Authority 
7 weeks ago by elizrael
[1803.08494] Group Normalization
Batch Normalization (BN) is a milestone technique in the development of deep learning, enabling various networks to train. However, normalizing along the batch dimension introduces problems --- BN's error increases rapidly when the batch size becomes smaller, caused by inaccurate batch statistics estimation. This limits BN's usage for training larger models and transferring features to computer vision tasks including detection, segmentation, and video, which require small batches constrained by memory consumption. In this paper, we present Group Normalization (GN) as a simple alternative to BN. GN divides the channels into groups and computes within each group the mean and variance for normalization. GN's computation is independent of batch sizes, and its accuracy is stable in a wide range of batch sizes. On ResNet-50 trained in ImageNet, GN has 10.6% lower error than its BN counterpart when using a batch size of 2; when using typical batch sizes, GN is comparably good with BN and outperforms other normalization variants. Moreover, GN can be naturally transferred from pre-training to fine-tuning. GN can outperform or compete with its BN-based counterparts for object detection and segmentation in COCO, and for video classification in Kinetics, showing that GN can effectively replace the powerful BN in a variety of tasks. GN can be easily implemented by a few lines of code in modern libraries.
neural-net  normalization  group-norm 
march 2018 by arsyed

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