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Martin E. Dyer

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23 papers
2 author rows

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23

SODA Conference 2016 Conference Paper

On the switch Markov chain for perfect matchings

  • Martin E. Dyer
  • Mark Jerrum
  • Haiko Müller

We study a simple Markov chain, the switch chain, on the set of all perfect matchings in a bipartite graph. This Markov chain was proposed by Diaconis, Graham and Holmes as a possible approach to a sampling problem arising in Statistics. They considered several classes of graphs, and conjectured that the switch chain would mix rapidly for graphs in these classes. Here we settle their conjecture almost completely. We ask: for which graph classes is the Markov chain ergodic and for which is it rapidly mixing? We provide a precise answer to the ergodicity question and close bounds on the mixing question. We show for the first time that the mixing time of the switch chain is polynomial in the class of monotone graphs. This class was identified by Diaconis, Graham and Holmes as being of particular interest in the statistical setting.

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STOC Conference 2010 Conference Paper

On the complexity of #CSP

  • Martin E. Dyer
  • David Richerby

Bulatov (2008) has given a dichotomy for the counting constraint satisfaction problem, #CSP. A problem from #CSP is characterized by a constraint language γ, which is a fixed, finite set of relations over a finite domain. An instance of the problem uses these relations to constrain the values taken by a finite set of variables. Bulatov showed that, for any fixed γ, the problem of counting the satisfying assignments of instances of any problem from #CSP is either in polynomial time (FP) or #P-complete, according on the structure of the constraint language γ. His proof draws heavily on techniques from universal algebra and cannot be understood without a secure grasp of that field. We give an elementary proof of Bulatov's dichotomy, based on succinct representations, which we call frames, of a class of highly structured relations, which we call strongly rectangular. We show that these are precisely the relations that are invariant under a Mal'tsev polymorphism. En route, we give a simplification of a decision algorithm for strongly rectangular constraint languages due to Bulatov and Dalmau (2006). Out proof uses no universal algebra, except for the straightforward concept of the Mal'tsev polymorphism and is accessible to readers with little background in #CSP.

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FOCS Conference 2004 Conference Paper

Randomly Coloring Constant Degree Graphs

  • Martin E. Dyer
  • Alan M. Frieze
  • Thomas P. Hayes
  • Eric Vigoda

We study a simple Markov chain, known as the Glauber dynamics, for generating a random k-coloring of a n-vertex graph with maximum degree /spl Delta/. We prove that the dynamics converges to a random coloring after O(n log n) steps assuming k /spl ges/ k/sub 0/ for some absolute constant k/sub 0/, and either: (i) k//spl Delta/ > /spl alpha/* /spl ap/ 1. 763 and the girth g /spl ges/ 5, or (ii) k//spl Delta/ > /spl beta/* /spl ap/ 1. 489 and the girth g /spl ges/ 6. Previous results on this problem applied when k = /spl Omega/(log n), or when k > 11 /spl Delta//6 for general graphs.

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STOC Conference 2003 Conference Paper

Approximate counting by dynamic programming

  • Martin E. Dyer

We give efficient algorithms to sample uniformly, and count approximately, the solutions to a zero-one knapsack problem. The algorithm is based on using dynamic programming to provide a deterministic relative approximation. Then "dart throwing" techniques are used to give arbitrary approximation ratios. We also indicate how further improvements can be obtained using randomized rounding. We extend the approach to several related problems: the m-constraint zero-one knapsack, the general integer knapsack (including its m-constraint version) and contingency tables with constantly many rows.

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STOC Conference 2002 Conference Paper

A polynomial-time algorithm to approximately count contingency tables when the number of rows is constant

  • Mary Cryan
  • Martin E. Dyer

We consider the problem of counting the number of contingency tables with given row and column sums. This problem is known to be #P-complete, even when there are only two rows [7]. In this paper we present the first fully-polynomial randomized approximation scheme for counting contingency tables when the number of rows is constant. A novel feature of our algorithm is that it is a hybrid of an exact counting technique with an approximation algorithm, giving two distinct phases. In the first, the columns are partitioned into "small" and "large". We show that the number of contingency tables can be expressed as the weighted sum of a polynomial number of new instances of the problem, where each instance consists of some new row sums and the original large column sums. In the second phase, we show how to approximately count contingency tables when all the column sums are large. In this case, we show that the solution lies in approximating the volume of a single convex body, a problem which is known to be solvable in polynomial time [5].

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FOCS Conference 2002 Conference Paper

Rapidly Mixing Markov Chains for Sampling Contingency Tables with a Constant Number of Rows

  • Mary Cryan
  • Martin E. Dyer
  • Leslie Ann Goldberg
  • Mark Jerrum
  • Russell A. Martin

We consider the problem of sampling almost uniformly from the set of contingency tables with given row and column sums, when the number of rows is a constant. (2002) have recently given a fully polynomial randomized approximation scheme (fpras) for the related counting problem, which only employs Markov chain methods indirectly. But they leave open the question as to whether a natural Markov chain on such tables mixes rapidly. Here we answer this question in the affirmative, and hence provide a very different proof of the main result of Cryan and Dyer. We show that the "2 /spl times/ 2 heat-bath" Markov chain is rapidly mixing. We prove this by considering first a heat-bath chain operating on a larger window. Using techniques developed by Morris and Sinclair (2002) (see also Morris (2002)) for the multidimensional knapsack problem, we show that this chain mixes rapidly. We then apply the comparison method of Diaconis and Saloff-Coste (1993) to show that the 2 /spl times/ 2 chain is rapidly mixing. As part of our analysis, we give the first proof that the 2 /spl times/ 2 chain mixes in time polynomial in the input size when both the number of rows and the number of columns is constant.

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FOCS Conference 2001 Conference Paper

Randomly Colouring Graphs with Lower Bounds on Girth and Maximum Degree

  • Martin E. Dyer
  • Alan M. Frieze

We consider the problem of generating a random q-colouring of a graph G=(V, E). We consider the simple Glauber Dynamics chain. We show that if the maximum degree /spl Delta/>c/sub l/ ln n and the girth g>c/sub 2/ ln ln n (n=|V|), then this chain mixes rapidly provided C/sub 1/, C/sub 2/ are sufficiently large, q/A>/spl beta/, where /spl beta//spl ap/1. 763 is the root of /spl beta/=e/sup 1//spl beta//. For this class of graphs, this beats the 11/spl Delta//6 bound of E. Vigoda (1999) for general graphs. We extend the result to random graphs.

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FOCS Conference 1999 Conference Paper

On Counting Independent Sets in Sparse Graphs

  • Martin E. Dyer
  • Alan M. Frieze
  • Mark Jerrum

We prove two results concerning approximate counting of independent sets in graphs with constant maximum degree /spl Delta/. The first result implies that the Monte-Carlo Markov chain technique is likely to fail if /spl Delta//spl ges/6. The second shows that no fully polynomial randomized approximation scheme can exist for /spl Delta//spl ges/25, unless P=NP under randomized reductions.

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FOCS Conference 1997 Conference Paper

Path Coupling: A Technique for Proving Rapid Mixing in Markov Chains

  • Russ Bubley
  • Martin E. Dyer

The main technique used in algorithm design for approximating #P-hard counting problems is the Markov chain Monte Carlo method. At the heart of the method is the study of the convergence (mixing) rates of particular Markov chains of interest. In this paper we illustrate a new approach to the coupling technique, which we call path coupling, for bounding mixing rates. Previous applications of coupling have required detailed insights into the combinatorics of the problem at hand, and this complexity can make the technique extremely difficult to apply successfully. Path coupling helps to minimize the combinatorial difficulty and in all cases provides simpler convergence proofs than does the standard coupling method. However the true power of the method is that the simplification obtained may allow coupling proofs which were previously unknown, or provide significantly better bounds than those obtained using the standard method. We apply the path coupling method to several hard combinatorial problems, obtaining new or improved results. We examine combinatorial problems such as graph colouring and TWICE-SAT, and problems from statistical physics, such as the antiferromagnetic Potts model and the hard-core lattice gas model. In each case we provide either a proof of rapid mixing where none was known previously, or substantial simplification of existing proofs with consequent gains in the performance of the resulting algorithms.

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