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Abstract

A function f(x 1, ... , x d ), where each input is an integer from 1 to n and output is a real number, is Lipschitz if changing one of the inputs by 1 changes the output by at most 1. In other words, Lipschitz functions are not very sensitive to small changes in the input. Our main result is an efficient tester for the Lipschitz property of functions f: [n]d → δℤ, where δ ∈ (0,1] and δℤ is the set of integer multiples of δ.

The main tool in the analysis of our tester is a smoothing procedure that makes a function Lipschitz by modifying it at a few points. Its analysis is already nontrivial for the 1-dimensional version, which we call Bubble Smooth, in analogy to Bubble Sort. In one step, Bubble Smooth modifies two values that violate the Lipschitz property, i.e., differ by more than 1, by transferring δ units from the larger to the smaller. We define a transfer graph to keep track of the transfers, and use it to show that the ℓ1 distance between f and BubbleSmooth(f) is at most twice the ℓ1 distance from f to the nearest Lipschitz function. Bubble Smooth has other important properties, which allow us to obtain a dimension reduction, i.e., a reduction from testing functions on multidimensional domains to testing functions on the 1-dimensional domain, that incurs only a small multiplicative overhead in the running time and thus avoids the exponential dependence on the dimension.

All omitted proofs appear in the full version [1].

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References

  1. Awasthi, P., Jha, M., Molinaro, M., Raskhodnikova, S.: Testing Lipschitz functions on hypergrid domains. Electronic Colloquium on Computational Complexity (ECCC) TR12-076 (2012)

    Google Scholar 

  2. Chakrabarty, D., Seshadhri, C.: Optimal bounds for monotonicity and Lipschitz testing over the hypercube. Electronic Colloquium on Computational Complexity (ECCC) TR12-030 (2012)

    Google Scholar 

  3. Dodis, Y., Goldreich, O., Lehman, E., Raskhodnikova, S., Ron, D., Samorodnitsky, A.: Improved Testing Algorithms for Monotonicity. In: Hochbaum, D.S., Jansen, K., Rolim, J.D.P., Sinclair, A. (eds.) RANDOM-APPROX 1999. LNCS, vol. 1671, pp. 97–108. Springer, Heidelberg (1999)

    Google Scholar 

  4. Goldreich, O., Goldwasser, S., Lehman, E., Ron, D., Samorodnitsky, A.: Testing monotonicity. Combinatorica 20(3), 301–337 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  5. Goldreich, O., Goldwasser, S., Ron, D.: Property testing and its connection to learning and approximation. J. ACM 45(4), 653–750 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  6. Gromov, M.: Metric Structures for Riemannian and non-Riemannian Spaces (1999)

    Google Scholar 

  7. Jha, M., Raskhodnikova, S.: Testing and reconstruction of Lipschitz functions with applications to data privacy. In: IEEE FOCS, pp. 433–442 (2011) full version available at, http://eccc.hpi-web.de/report/2011/057/

  8. Rubinfeld, R., Sudan, M.: Robust characterization of polynomials with applications to program testing. SIAM J. Comput. 25(2), 252–271 (1996)

    Article  MathSciNet  MATH  Google Scholar 

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Awasthi, P., Jha, M., Molinaro, M., Raskhodnikova, S. (2012). Testing Lipschitz Functions on Hypergrid Domains. In: Gupta, A., Jansen, K., Rolim, J., Servedio, R. (eds) Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques. APPROX RANDOM 2012 2012. Lecture Notes in Computer Science, vol 7408. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32512-0_33

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  • DOI: https://doi.org/10.1007/978-3-642-32512-0_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32511-3

  • Online ISBN: 978-3-642-32512-0

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