Self-testing/correcting for polynomials and for approximate functions
STOC '91 Proceedings of the twenty-third annual ACM symposium on Theory of computing
Checking approximate computations over the reals
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Self-testing/correcting with applications to numerical problems
Journal of Computer and System Sciences - Special issue: papers from the 22nd ACM symposium on the theory of computing, May 14–16, 1990
Designing programs that check their work
Journal of the ACM (JACM)
Property testing in bounded degree graphs
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Approximate testing with relative error
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
On the Robustness of Functional Equations
SIAM Journal on Computing
Robust Characterizations of Polynomials withApplications to Program Testing
SIAM Journal on Computing
Transparent (Holographic) Proofs
STACS '93 Proceedings of the 10th Annual Symposium on Theoretical Aspects of Computer Science
Approximate checking of polynomials and functional equations
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
Property testing and its connection to learning and approximation
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
Proof verification and hardness of approximation problems
SFCS '92 Proceedings of the 33rd Annual Symposium on Foundations of Computer Science
Probabilistic checking of proofs; a new characterization of NP
SFCS '92 Proceedings of the 33rd Annual Symposium on Foundations of Computer Science
Exact and Approximate Testing/Correcting of Algebraic Functions: A Survey
Theoretical Aspects of Computer Science, Advanced Lectures [First Summer School on Theoretical Aspects of Computer Science, Tehran, Iran, July 2000]
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We investigate self-testing programs with relative error by allowing error terms proportional to the function to be computed. Until now, in numerical computation, error terms were assumed to be either constant or proportional to the p-th power of the magnitude of the input, for p ∈ [0, 1]. We construct new self-testers with relative error for realvalued multi-linear functions defined over finite rational domains. The existence of such self-testers positively solves an open question in [KMS99]. Moreover, our self-testers are very efficient: they use few queries and simple operations.