20 monthly gift articles to share
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The efficiency depends on the query size relative to the data distribution. A small query in a sparse region prunes almost everything. A query that covers the whole space prunes nothing (because every node overlaps), degenerating to a brute-force scan. The quadtree gives you the most benefit when your queries are spatially local, which is exactly the common case for map applications, game physics, and spatial databases.
Trained weights via any generic learning algorithm (shows the solution is learnable — encourages creative ideas on data format, tokenization, and curriculum)