Eldar Fischer

A combinatorial characterization of the testable graph properties: it's all about regularity

A common thread in recent results concerning the testing of dense graphs is the use of Szemerédis regularity lemma. In this paper we show that in some sense this is not a coincidence. Our first result is that the property defined by having any given Szemerédi-partition is testable with a constant number of queries. Our second and main result is a purely combinatorial characterization of the graph properties that are testable with a constant number of queries. This characterization (roughly) says that a graph property P can be tested with a constant number of queries if and only if testing P can be reduced to testing the property of satisfying one of finitely many Szemerédi-partitions. This means that in some sense, testing for Szemerédi-partitions is as hard as testing any testable graph property. We thus resolve one of the main open problems in the area of property-testing, which was raised in the 1996 paper of Goldreich, Goldwasser and Ron [25] that initiated the study of graph property-testing. This characterization also gives an intuitive explanation as to what makes a graph property testable.

Hardness and algorithms for rainbow connection

An edge-colored graph G is rainbow connected if any two vertices are connected by a path whose edges have distinct colors. The rainbow connection of a connected graph G, denoted rc(G), is the smallest number of colors that are needed in order to make G rainbow connected. In the first result of this paper we prove that computing rc(G) is NP-Hard solving an open problem from Caro et al. (Electron. J. Comb. 15, 2008, Paper R57). In fact, we prove that it is already NP-Complete to decide if rc(G)=2, and also that it is NP-Complete to decide whether a given edge-colored (with an unbounded number of colors) graph is rainbow connected. On the positive side, we prove that for every ε>0, a connected graph with minimum degree at least εn has bounded rainbow connection, where the bound depends only on ε, and a corresponding coloring can be constructed in polynomial time. Additional non-trivial upper bounds, as well as open problems and conjectures are also presented.

Testing random variables for independence and identity

Given access to independent samples of a distribution A over [n] /spl times/ [m], we show how to test whether the distributions formed by projecting A to each coordinate are independent, i.e., whether A is /spl epsi/-close in the L/sub 1/ norm to the product distribution A/sub 1//spl times/A/sub 2/ for some distributions A/sub 1/ over [n] and A/sub 2/ over [m]. The sample complexity of our test is O/spl tilde/(n/sup 2/3/m/sup 1/3/poly(/spl epsi//sup -1/)), assuming without loss of generality that m/spl les/n. We also give a matching lower bound, up to poly (log n, /spl epsi//sup -1/) factors. Furthermore, given access to samples of a distribution X over [n], we show how to test if X is /spl epsi/-close in L/sub 1/ norm to an explicitly specified distribution Y. Our test uses O/spl tilde/(n/sup 1/2/poly(/spl epsi//sup -1/)) samples, which nearly matches the known tight bounds for the case when Y is uniform.

A Combinatorial Characterization of the Testable Graph Properties: It's All About Regularity

A common thread in all of the recent results concerning the testing of dense graphs is the use of Szemeredis regularity lemma. In this paper we show that in some sense this is not a coincidence. Our first result is that the property defined by having any given Szemeredi-partition is testable with a constant number of queries. Our second and main result is a purely combinatorial characterization of the graph properties that are testable with a constant number of queries. This characterization (roughly) says that a graph property

Testing juntas

{\cal P}

PCP characterizations of NP: towards a polynomially-small error-probability

can be tested with a constant number of queries if and only if testing

Testing versus Estimation of Graph Properties

{\cal P}

Testing versus estimation of graph properties

can be reduced to testing the property of satisfying one of finitely many Szemeredi-partitions. This means that in some sense, testing for Szemeredi-partitions is as hard as testing any testable graph property. We thus resolve one of the main open problems in the area of property-testing, which was first raised by Goldreich, Goldwasser, and Ron [J. ACM, 45 (1998), pp. 653-750] in the paper that initiated the study of graph property-testing. This characterization also gives an intuitive explanation as to what makes a graph property testable.

Testing Graph Isomorphism

We show that a Boolean function over n Boolean variables can be tested for the property of depending on only k of them, using a number of queries that depends only on k and the approximation parameter \varepsilon. We present two tests, both non-adaptive, that require a number of queries that is polynomial k and linear in \varepsilon ^{- 1}. The first test is stronger in that it has a 1-sided error, while the second test has a more compact analysis. We also present an adaptive version and a 2-sided error version of the first test, that have a somewhat better query complexity than the other algorithms.We then provide a lower bound of \bar \Omega (\sqrt k) on the number of queries required for the non-adaptive testing of the above property; a lower bound of \Omega (\log (k + 1)) for adaptive algorithms naturally follows from this. In providing this we also prove a result about random walks on the group {\rm Z}_2^9 that may be interesting in its own right. We show that for some t(q) = \bar 0(q^2) the distributions of the random walk at times t and t + 2 are close to each other, independently of the step distribution of the walk.We also discuss related questions. In particular, when given in advance a known k-junta function h, we show how to test a function f for the property of being identical to h up to a permutation of the variables, in a number of queries that is polynomial in k and \varepsilon.

2-factors in dense graphs

This paper strengthens the low-error PCP characterization of NP, coming closer to the upper limit of the BGLR conjecture. Consider the task of verifying a written proof for the membership of a given input in an NP language. In this paper, this is achieved by making a constant number of accesses to the proof, obtaining error probability that is exponentially small in the total number of bits that are read.