Log-Concave Polynomials II: High-Dimensional Walks and an FPRAS for Counting Bases of a Matroid
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Abstract (arXiv)
We design an FPRAS to count the number of bases of any matroid given by an independent set oracle, and to estimate the partition function of the random cluster model of any matroid in the regime where 0<q<1. Consequently, we can sample random spanning forests in a graph and (approximately) compute the reliability polynomial of any matroid. We also prove the thirty year old conjecture of Mihail and Vazirani that the bases exchange graph of any matroid has expansion at least 1. One of our key observations is a close connection between pure simplicial complexes and multiaffine homogeneous polynomials. Specifically, if X is a pure simplicial complex with positive weights on its maximal faces, we can associate with X a multiaffine homogeneous polynomial pX such that the eigenvalues of the localized random walks on X correspond to the eigenvalues of the Hessian of derivatives of pX.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Nov 2018.
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Citing papers per year: 2021: 3; 2022: 0; 2023: 1; 2024: 2; 2025: 1.
7 papers.
- 2024Batch Active Learning of Reward Functions from Human Preferencescited by 8
- 2021From Sampling to Optimization on Discrete Domains with Applications to Determinant Maximizationcited by 3
- 2021Some Inapproximability Results of MAP Inference and Exponentiated Determinantal Point Processescited by 3
- 2023Learning Arithmetic Formulas in the Presence of Noise: A General Framework and Applications to Unsupervised Learningcited by 1
- 2025Arithmetic Circuits and Neural Networks for Regular Matroidscited by 1
- 2021Computational Complexity of Normalizing Constants for the Product of Determinantal Point Processescited by 0
- 2024Almost linear time differentially private release of synthetic graphscited by 0
- 2025Arithmetic Circuits and Neural Networks for Regular Matroids4 Nov 2025
- 2024Almost linear time differentially private release of synthetic graphs4 Jun 2024
- 2024Batch Active Learning of Reward Functions from Human Preferences24 Feb 2024
- 2023Learning Arithmetic Formulas in the Presence of Noise: A General Framework and Applications to Unsupervised Learning13 Nov 2023
- 2021Computational Complexity of Normalizing Constants for the Product of Determinantal Point Processes28 Nov 2021
- 2021Some Inapproximability Results of MAP Inference and Exponentiated Determinantal Point Processes2 Sep 2021
- 2021From Sampling to Optimization on Discrete Domains with Applications to Determinant Maximization10 Feb 2021