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Electronic Colloquium on Computational Complexity

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Reports tagged with Probabilistic Complexity Classes:
TR95-061 | 27th November 1995
Alexander E. Andreev, Andrea E. F. Clementi, Jose' D. P. Rolim

Hitting sets derandomize BPP

Revisions: 1

We show that hitting sets can derandomize any BPP-algorithm.
This gives a positive answer to a fundamental open question in
probabilistic algorithms. More precisely, we present a polynomial
time deterministic algorithm which uses any given hitting set
to approximate the fractions of 1's in the ... more >>>

TR98-037 | 29th June 1998
Johannes Köbler, Rainer Schuler

Average-Case Intractability vs. Worst-Case Intractability

We use the assumption that all sets in NP (or other levels
of the polynomial-time hierarchy) have efficient average-case
algorithms to derive collapse consequences for MA, AM, and various
subclasses of P/poly. As a further consequence we show for
C in {P(PP), PSPACE} that ... more >>>

TR00-034 | 5th June 2000
Valentine Kabanets, Charles Rackoff, Stephen Cook

Efficiently Approximable Real-Valued Functions

We consider a class, denoted APP, of real-valued functions
f:{0,1}^n\rightarrow [0,1] such that f can be approximated, to
within any epsilon>0, by a probabilistic Turing machine running in
time poly(n,1/epsilon). We argue that APP can be viewed as a
generalization of BPP, and show that APP contains a natural
complete ... more >>>

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