Charilaos Efthymiou, Thomas P. Hayes, Daniel Stefankovic, Eric Vigoda, Yitong Yin
{"title":"硬核模型树唯一性区域MCMC和Loopy BP的收敛性","authors":"Charilaos Efthymiou, Thomas P. Hayes, Daniel Stefankovic, Eric Vigoda, Yitong Yin","doi":"10.1109/FOCS.2016.80","DOIUrl":null,"url":null,"abstract":"We study the hard-core (gas) model defined on independent sets of an input graph where the independent sets are weighted by a parameter (aka fugacity) λ > 0. For constant Δ, previous work of Weitz (2006) established an FPTAS for the partition function for graphs of maximum degree Δ when λ <; λ<sub>c</sub>(Δ). Sly (2010) showed that there is no FPRAS, unless NP=RP, when λ > λ<sub>c</sub>(Δ). The threshold λ<sub>c</sub>(Δ) is the critical point for the statistical physics phase transition for uniqueness/non-uniqueness on the infinite Δ-regular tree. The running time of Weitz's algorithm is exponential in log Δ. Here we present an FPRAS for the partition function whose running time is O* (n<sup>2</sup>). We analyze the simple single-site Markov chain known as the Glauber dynamics for sampling from the associated Gibbs distribution. We prove there exists a constant Δ<sub>0</sub> such that for all graphs with maximum degree Δ > Δ<sub>0</sub> and girth > 7 (i.e., no cycles of length ≤ 6), the mixing time of the Glauber dynamics is O(nlog n) when λ <; λ<sub>c</sub>(Δ). Our work complements that of Weitz which applies for small constant Δ whereas our work applies for all Δ at least a sufficiently large constant Δ<sub>0</sub> (this includes Δ depending on n = IVI). Our proof utilizes loopy BP (belief propagation) which is a widely-used algorithm for inference in graphical models. A novel aspect of our work is using the principal eigenvector for the BP operator to design a distance function which contracts in expectation for pairs of states that behave like the BP fixed point. We also prove that the Glauber dynamics behaves locally like loopy BP. As a byproduct we obtain that the Glauber dynamics, after a short burn-in period, converges close to the BP fixed point, and this implies that the fixed point of loopy BP is a close approximation to the Gibbs distribution. Using these connections we establish that loopy BP quickly converges to the Gibbs distribution when the girth ≥ 6 and λ <; λ<sub>c</sub>(Δ).","PeriodicalId":414001,"journal":{"name":"2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS)","volume":" 8","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"36","resultStr":"{\"title\":\"Convergence of MCMC and Loopy BP in the Tree Uniqueness Region for the Hard-Core Model\",\"authors\":\"Charilaos Efthymiou, Thomas P. Hayes, Daniel Stefankovic, Eric Vigoda, Yitong Yin\",\"doi\":\"10.1109/FOCS.2016.80\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We study the hard-core (gas) model defined on independent sets of an input graph where the independent sets are weighted by a parameter (aka fugacity) λ > 0. For constant Δ, previous work of Weitz (2006) established an FPTAS for the partition function for graphs of maximum degree Δ when λ <; λ<sub>c</sub>(Δ). Sly (2010) showed that there is no FPRAS, unless NP=RP, when λ > λ<sub>c</sub>(Δ). The threshold λ<sub>c</sub>(Δ) is the critical point for the statistical physics phase transition for uniqueness/non-uniqueness on the infinite Δ-regular tree. The running time of Weitz's algorithm is exponential in log Δ. Here we present an FPRAS for the partition function whose running time is O* (n<sup>2</sup>). We analyze the simple single-site Markov chain known as the Glauber dynamics for sampling from the associated Gibbs distribution. We prove there exists a constant Δ<sub>0</sub> such that for all graphs with maximum degree Δ > Δ<sub>0</sub> and girth > 7 (i.e., no cycles of length ≤ 6), the mixing time of the Glauber dynamics is O(nlog n) when λ <; λ<sub>c</sub>(Δ). Our work complements that of Weitz which applies for small constant Δ whereas our work applies for all Δ at least a sufficiently large constant Δ<sub>0</sub> (this includes Δ depending on n = IVI). Our proof utilizes loopy BP (belief propagation) which is a widely-used algorithm for inference in graphical models. A novel aspect of our work is using the principal eigenvector for the BP operator to design a distance function which contracts in expectation for pairs of states that behave like the BP fixed point. We also prove that the Glauber dynamics behaves locally like loopy BP. As a byproduct we obtain that the Glauber dynamics, after a short burn-in period, converges close to the BP fixed point, and this implies that the fixed point of loopy BP is a close approximation to the Gibbs distribution. Using these connections we establish that loopy BP quickly converges to the Gibbs distribution when the girth ≥ 6 and λ <; λ<sub>c</sub>(Δ).\",\"PeriodicalId\":414001,\"journal\":{\"name\":\"2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS)\",\"volume\":\" 8\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"36\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FOCS.2016.80\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FOCS.2016.80","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Convergence of MCMC and Loopy BP in the Tree Uniqueness Region for the Hard-Core Model
We study the hard-core (gas) model defined on independent sets of an input graph where the independent sets are weighted by a parameter (aka fugacity) λ > 0. For constant Δ, previous work of Weitz (2006) established an FPTAS for the partition function for graphs of maximum degree Δ when λ <; λc(Δ). Sly (2010) showed that there is no FPRAS, unless NP=RP, when λ > λc(Δ). The threshold λc(Δ) is the critical point for the statistical physics phase transition for uniqueness/non-uniqueness on the infinite Δ-regular tree. The running time of Weitz's algorithm is exponential in log Δ. Here we present an FPRAS for the partition function whose running time is O* (n2). We analyze the simple single-site Markov chain known as the Glauber dynamics for sampling from the associated Gibbs distribution. We prove there exists a constant Δ0 such that for all graphs with maximum degree Δ > Δ0 and girth > 7 (i.e., no cycles of length ≤ 6), the mixing time of the Glauber dynamics is O(nlog n) when λ <; λc(Δ). Our work complements that of Weitz which applies for small constant Δ whereas our work applies for all Δ at least a sufficiently large constant Δ0 (this includes Δ depending on n = IVI). Our proof utilizes loopy BP (belief propagation) which is a widely-used algorithm for inference in graphical models. A novel aspect of our work is using the principal eigenvector for the BP operator to design a distance function which contracts in expectation for pairs of states that behave like the BP fixed point. We also prove that the Glauber dynamics behaves locally like loopy BP. As a byproduct we obtain that the Glauber dynamics, after a short burn-in period, converges close to the BP fixed point, and this implies that the fixed point of loopy BP is a close approximation to the Gibbs distribution. Using these connections we establish that loopy BP quickly converges to the Gibbs distribution when the girth ≥ 6 and λ <; λc(Δ).