Sampling binary contingency tables with a greedy start

DOI10.1002/rsa.20155zbMath1104.62068OpenAlexW4236531880MaRDI QIDQ5898351

Ivona Bezáková, Eric Vigoda, Nayantara Bhatnagar

Publication date: 7 February 2007

Published in: Random Structures & Algorithms (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/rsa.20155

zbMATH Keywords

bootstrappinggreedy graph

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Contingency tables (62H17)

Related Items (13)

Monte Carlo algorithms for computing \(\alpha \)-permanents ⋮ On the Diaconis-Gangolli Markov Chain for Sampling Contingency Tables with Cell-Bounded Entries ⋮ On the mixing time of the Diaconis-Gangolli random walk on contingency tables over \(\mathbb{Z}/q\mathbb{Z} \) ⋮ Negative examples for sequential importance sampling of binary contingency tables ⋮ On the Diaconis-Gangolli Markov chain for sampling contingency tables with cell-bounded entries ⋮ Sampling hypergraphs with given degrees ⋮ The mixing time of switch Markov chains: a unified approach ⋮ New Classes of Degree Sequences with Fast Mixing Swap Markov Chain Sampling ⋮ Characterizing optimal sampling of binary contingency tables via the configuration model ⋮ On the number of matrices and a random matrix with prescribed row and column sums and 0-1 entries ⋮ Uniform Sampling of Digraphs with a Fixed Degree Sequence ⋮ Approximately Counting Embeddings into Random Graphs ⋮ A Decomposition Based Proof for Fast Mixing of a Markov Chain over Balanced Realizations of a Joint Degree Matrix

Cites Work

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• A theorem on flows in networks
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• Improved Bounds for Mixing Rates of Markov Chains and Multicommodity Flow
• Generating random regular graphs
• Monte Carlo strategies in scientific computing

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