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Stochastic processes
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#	Item
171	Spectral Graph Theory Lecture 9 PSRGs via Random Walks on Graphs Daniel A. Spielman Add to Reading List Source URL: www.cs.yale.edu Language: English - Date: 2012-08-24 09:50:05 Stochastic processes Random walk Expander graph Randomized algorithm Algebraic graph theory Graph theory Loop-erased random walk Laplacian matrix
172	TERM STRUCTURE OF INTEREST RATES Term Structure of Interest Rates This is the first of two articles on the term structure. In it, the authors discuss some term structure fundamentals and the measurement of the current t Add to Reading List Source URL: pluto.mscc.huji.ac.il Language: English - Date: 2014-02-02 05:57:49 Mathematical finance Fixed income analysis Interest rates Stochastic processes Actuarial science CoxIngersollRoss model Vasicek model Bond valuation Yield curve BlackDermanToy model Discounting Time value of money
173	arXiv:0711.4225v1 [q-fin.GN] 27 NovConsumption processes and positively homogeneous projection properties Tom Fischer∗ Heriot-Watt University, Edinburgh Add to Reading List Source URL: arxiv.org Language: English - Date: 2013-12-22 22:47:46 Martingale theory Stochastic processes Game theory Martingale Paul Lvy
174	Project number ISTCGL Computational Geometric Learning Random Pursuit in Hilbert Space Add to Reading List Source URL: cgl.uni-jena.de Language: English - Date: 2013-11-21 09:39:43 Stochastic processes Stochastic optimization Mathematical optimization Operations research Random walk CMA-ES Probability theory
175	CS168: The Modern Algorithmic Toolbox Lecture #14: Markov Chain Monte Carlo Tim Roughgarden & Gregory Valiant∗ May 11, 2016 The previous lecture covered several tools for inferring properties of the distribution that u Add to Reading List Source URL: theory.stanford.edu Language: English - Date: 2016-06-04 09:49:43 Markov models Markov processes Stochastic processes Monte Carlo methods Statistical mechanics Markov chain Stochastic matrix Markov property Random walk Continuous-time Markov chain Bayesian inference in phylogeny
176	PHYSICAL REVIEW E 80, 036119 共2009兲 Exact encounter times for many random walkers on regular and complex networks David P. Sanders* Departamento de Física, Facultad de Ciencias, and Centro de Ciencias de la Complej Add to Reading List Source URL: sistemas.fciencias.unam.mx Language: English - Date: 2011-03-31 15:04:54 Stochastic processes Random walk Probability current Markov chain
177	A Statistical Model for Event Sequence Data Kevin Heins Department of Statistics University of California, Irvine Add to Reading List Source URL: contecenter.uci.edu Language: English - Date: 2014-08-06 21:12:14 Statistical models Stochastic processes Poisson processes Probability theory Probability distributions Markov chain Exponential distribution Renewal theory Mixture model Sequence alignment
178	PHYSICAL REVIEW E 93, Efficient community detection of network flows for varying Markov times and bipartite networks Masoumeh Kheirkhahzadeh,1,2 Andrea Lancichinetti,2 and Martin Rosvall2,* 1 Add to Reading List Source URL: www.mapequation.org Language: English - Date: 2016-03-19 03:43:10 Stochastic processes Markov processes Markov models Probability theory Network theory Markov chain Modularity Ergodicity Random walk
179	Studies in Nonlinear Dynamics & Econometrics Volume , Issue   Add to Reading List Source URL: johnstachurski.net Language: English - Date: 2016-06-19 06:01:40 Markov models Stochastic processes Probability theory Competition Decision theory Path dependence Markov chain Attractor Normal distribution Ergodicity
180	Automatically Grading Learners’ English Using a Gaussian Process Rogier C. van Dalen, Kate M. Knill, Mark J. F. Gales ALTA Institute / Department of Engineering, University of Cambridge, United Kingdom {rcv25,kmk1001,m Add to Reading List Source URL: mi.eng.cam.ac.uk Language: English - Date: 2015-06-24 05:28:12 Geostatistics Covariance and correlation Stochastic processes Interpolation Gaussian process Normal distribution Covariance function Kernel method Speech recognition Radial basis function Correlation and dependence Variance

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