The notation o(n^2) refers to a class of functions that grow at a rate significantly slower than n^2 as n approaches infinity. In the context of algorithms, it indicates that the algorithm's running time increases more slowly than the square of the input size, suggesting that such algorithms are more efficient for larger inputs compared to those with a time complexity of Θ(n^2). This is crucial for analyzing the efficiency of algorithms, especially in computational geometry where performance is key.
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