Sublinear time algorithms represent a paradigm shift in computational efficiency, allowing processing of extremely large datasets by reading only a fraction of the input. While exact deterministic sublinear algorithms exist for some problems, most solutions require randomization and approximation techniques, with applications spanning optimization, property testing, and distribution analysis.

https://people.csail.mit.edu/ronitt/sublinear.html

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