首页> 外文学位 >Estimating mixing times: Techniques and applications.
【24h】

Estimating mixing times: Techniques and applications.

机译:估计混合时间:技术和应用。

获取原文
获取原文并翻译 | 示例

摘要

How many times do you have to shuffle a deck of n cards before it is close to random? log n? n? n3? Similar convergence rate questions for finite Markov chains are central to solving applied problems in diverse fields including physics, computer science and biology. This thesis investigates two general techniques for estimating mixing times for finite Markov chains: modified logarithmic Sobolev inequalities and Faber-Krahn inequalities; and analyzes the convergence behavior of a specific family of random walks: the top to bottom shuffles.; Logarithmic Sobolev inequalities are a well-studied technique for estimating convergence rates for Markov chains. In contrast to continuous state spaces, there are several distinct modified log Sobolev inequalities in the discrete setting. Here we derive modified log Sobolev inequalities for several models of random walk, including the random transposition shuffle. These results lead to tight mixing time estimates, and additionally, yield concentration inequalities.; Faber-Krahn inequalities have been used to estimate the rate of decay of the heat kernel on complete, non-compact manifolds and infinite graphs. We develop this technique in the setting of finite Markov chains, proving upper and lower Linfinity mixing time bounds via the spectral profile. This approach lets us recover previous conductance-based bounds of mixing time, and in general leads to sharper estimates of convergence rates. We apply this method to several models, including groups with moderate growth, the fractal-like Viscek graphs, and the product group ZaxZ b , and obtain tight bounds on the corresponding mixing times.; A deck of n cards is shuffled by repeatedly moving the top card to one of the bottom kn positions of the deck uniformly at random. We give upper and lower bounds on the total variation mixing time for this shuffle as kn ranges from a constant to n. We also consider a symmetric variant of this walk which at each step either inserts the top card randomly into the bottom kn positions or moves a random card from the bottom kn positions to the top. For this reversible shuffle we derive L2 mixing time bounds.
机译:在随机抽取几张n张卡片之前,您需要洗几次?登录n? n? n3?有限马尔可夫链的相似收敛速度问题对于解决物理,计算机科学和生物学等各个领域的应用问题至关重要。本文研究了两种用于估计有限马氏链混合时间的通用技术:修正对数Sobolev不等式和Faber-Krahn不等式;并分析了特定的随机游走族的收敛行为:从上到下的随机播放。对数Sobolev不等式是一种用于研究马尔可夫链收敛速度的经过充分研究的技术。与连续状态空间相反,在离散设置中有几个不同的修改对数Sobolev不等式。在这里,我们推导了几种随机游走模型的修正对数Sobolev不等式,包括随机换位随机播放。这些结果导致紧密的混合时间估计,以及收率浓度不均。 Faber-Krahn不等式已用于估计完整,非紧实流形和无限图上热核的衰减率。我们在有限的马尔可夫链的设置中开发了此技术,通过光谱曲线证明了上限和下限Linfinity混合时间范围。这种方法使我们能够恢复以前基于电导的混合时间界限,并且通常可以更精确地估计收敛速度。我们将此方法应用于几个模型,包括中等增长的组,分形的Viscek图和乘积组ZaxZ b,并在相应的混合时间上获得严格的界限。通过随机将顶牌重复均匀地移动到牌组的底部kn个位置之一,可对一副n张牌进行洗牌。由于kn从常数到n,我们为这种混洗给出了总变化混合时间的上限和下限。我们还考虑了这种走法的对称变体,在每个步骤中,要么将顶部卡片随机插入底部kn位置,要么将随机卡片从底部kn位置移至顶部。对于这种可逆混洗,我们得出L2混合时间范围。

著录项

  • 作者

    Goel, Sharad Chandra.;

  • 作者单位

    Cornell University.;

  • 授予单位 Cornell University.;
  • 学科 Mathematics.
  • 学位 Ph.D.
  • 年度 2005
  • 页码 137 p.
  • 总页数 137
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 数学;
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号