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May 30, 2023 at 6:26 comment added JeeyCi Dense is saturated with non-zeros, Sparse comprises mane zero weights in matrix = Hence, sparce is difficult/slow to estimate, having lack of points & their dynamics in matrix/batches => need something like Convolution to eliminate zero-weights first (~regularization) to speed-up training, I think. Sparcity is the case of Images, computer vision, NLP, as is learning language models, cinema & phone-commutation signals, can use sparse-dence embeddings for better search results
Jan 13, 2023 at 9:00 history tweeted twitter.com/StackStats/status/1613823166790483969
Jan 13, 2023 at 0:52 answer added TeddybearCrisis timeline score: 0
Oct 4, 2018 at 7:38 history edited kjetil b halvorsen
edited tags
Oct 2, 2018 at 11:20 comment added Scortchi See also What does “sparse” mean in the context of neural nets?
S Oct 2, 2018 at 11:17 history suggested user82135 CC BY-SA 4.0
A few small changes.
Oct 2, 2018 at 10:50 review Suggested edits
S Oct 2, 2018 at 11:17
Mar 12, 2017 at 17:09 vote accept Dmytro Nalyvaiko
Mar 12, 2017 at 16:41 answer added user20160 timeline score: 24
Mar 12, 2017 at 15:07 history edited gung - Reinstate Monica CC BY-SA 3.0
added tags; edited for English
Mar 12, 2017 at 14:44 review Low quality posts
Mar 12, 2017 at 15:07
Mar 12, 2017 at 14:29 history asked Dmytro Nalyvaiko CC BY-SA 3.0