Post #252

#ML https://www.microsoft.com/en-us/research/blog/make-every-feature-binary-a-135b-parameter-sparse-neural-network-for-massively-improved-search-relevance/ Though not the core of the model, I noticed that this model (MEB) uses the user search behavior on Bing to build the language model. If a search result on Bing is clicked by the user, it is considered to be a positive sample for the query, otherwise a negative sample. In self-supervised learning, it has been shown that negative sampling is extremely important. This Bing search dataset is naturally labeling the positive and negative samples. Kuhl idea.