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Memory-Restricted and Secure Algorithms For Large Datasets
With the rise of big data, there is a growing need to solve optimization tasks on massive datasets. Running optimization tasks on large-scale datasets can be quite challenging as classical algorithms often have unrealistic assumptions about the data. For example, classical algorithms oftentimes assume that the computing machines have enough memory to store all of the data. However, in the era of big data, we often face massive datasets that are too large to fit into the computer's memory. Indoi:10.13016/owez-vvvz fatcat:qpk4ex6u3ba5dhczjbwwjrnj6i