Title :
Geometric discrepancy revisited
Author :
Chazelle, Bernard
Author_Institution :
Dept. of Comput. Sci., Princeton Univ., NJ, USA
Abstract :
Discrepancy theory addresses the general issue of approximating one measure by another one. Originally an offshoot of diophantine approximation theory, the area has expanded into applied mathematics, and now, computer science. Besides providing the theoretical foundation for sampling, it holds some of the keys to understanding the computational power of randomization. A few applications of discrepancy theory are listed. We give elementary algorithms for estimating the discrepancy between various measures arising in practice. We also present a general technique for proving discrepancy lower bounds
Keywords :
computational complexity; computational geometry; randomised algorithms; computational power; diophantine approximation theory; discrepancy lower bounds; discrepancy theory; elementary algorithms; geometric discrepancy; randomization; sampling; Algorithm design and analysis; Application software; Approximation methods; Atomic measurements; Computer errors; Computer graphics; Computer science; Finite element methods; Mathematics; Sampling methods;
Conference_Titel :
Foundations of Computer Science, 1993. Proceedings., 34th Annual Symposium on
Conference_Location :
Palo Alto, CA
Print_ISBN :
0-8186-4370-6
DOI :
10.1109/SFCS.1993.366848