Abstract
Discrepancy theory is the study of irregularities of distributions. A typical question is: given a “complicated” distribution, find a “simple” one that approximates it well. As it turns out, many questions in complexity theory can be reduced to problems of that type. This raises the possibility that the deep mathematical techniques of discrepancy theory might be of utility to theoretical computer scientists. As will be discussed in this talk this is, indeed, the case. We will give several examples of breakthroughs derived through the application of the “discrepancy method.”
This work was supported in part by NSF Grant CCR-93-01254, NSF Grant CCR-96-23768, ARO Grant DAAH04-96-1-0181, and NEC Research Institute.
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Chazelle, B. (1998). The Discrepancy Method. In: Chwa, KY., Ibarra, O.H. (eds) Algorithms and Computation. ISAAC 1998. Lecture Notes in Computer Science, vol 1533. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49381-6_1
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