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Sensitivity and block sensitivity are useful and well-studied measures of computational complexity, but in spite of their similarities, the largest possible gap between them is still unknown. Rubinstein showed that this gap must be at least quadratic, and Kenyon and Kutin showed that it is at worst exponential, but many strongly suspect that the gap is indeed quadratic, or at worst polynomial.
Our work shows that for a large class of functions, which includes Rubinstein's function, the quadratic gap between sensitivity and block sensitivity is the best we can possibly do.
Senior Honours Thesis Advisor: Amit Chakrabarti
Bibliographic citation for this report: [plain text] [BIB] [BibTeX] [Refer]
Or copy and paste:
Karn Seth, "Block Sensitivity versus Sensitivity." Dartmouth Computer Science Technical Report TR2010-673, June 2010.
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