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391	Exact encounter times for many random walkers on regular and complex networks David P. Sanders∗ Departamento de F´ısica, Facultad de Ciencias, Universidad Nacional Aut´onoma de M´exico, Ciudad Universitaria, 04510 Add to Reading List Source URL: sistemas.fciencias.unam.mx - Date: 2011-03-31 15:05:14
392	MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Deep Gaussian Conditional Random Field Network: A Model-based Deep Network for Discriminative Denoising Vemulapalli, R.; Tuzel, C.O.; Liu, M.-Y. Add to Reading List Source URL: www.merl.com - Date: 2016-08-18 16:46:39
393	Spectral Graph Theory Lecture 22 Sparsification by Random Sampling Daniel A. Spielman Add to Reading List Source URL: www.cs.yale.edu - Date: 2015-08-17 14:43:26
394	Reconstruction of a persistent random walk from exit time distributions Pak-Wing Fok1 , Qunhui Han1, and Tom Chou2 1 2 Add to Reading List Source URL: udel.edu - Date: 2013-03-06 10:08:22
395	BPLRU: A Buffer Management Scheme for Improving Random Writes in Flash Storage Hyojun Kim and Seongjun Ahn Software Laboratory of Samsung Electronics, Korea {zartoven, seongjun.ahn}@samsung.com Add to Reading List Source URL: www.usenix.org - Date: 2008-02-27 11:17:10
396	Department of Biomathematics Seminar Series: Frontiers in Systems and Integrative Biology Anomalous Diffusion and Random Encounters in Living Systems Scott A. McKinley, Ph.D. Add to Reading List Source URL: www.biomath.ucla.edu - Date: 2015-11-24 12:27:35
397	MOMENT GENERATING FUNCTIONS FOR LOCAL TIMES OF SYMMETRIC MARKOV PROCESSES AND RANDOM WALKS Michael B. Marcus and Jay Rosen 1. Introduction. We obtain moment generating functions for the local times of strongly symmetric Add to Reading List Source URL: www.math.csi.cuny.edu - Date: 2009-05-03 17:56:51
398	Assessing stochastic algorithms for large scale nonlinear least squares problems using extremal probabilities of linear combinations of gamma random variables Farbod Roosta-Khorasani∗ Add to Reading List Source URL: www.stat.berkeley.edu - Date: 2016-01-22 15:04:49
399	In this talk, I will introduce hinge-loss Markov random fields (HLMRFs), a new kind of probabilistic graphical model that supports scalable collective inference from richly structured data. HL-MRFs unify three different Add to Reading List Source URL: mmds-data.org - Date: 2016-06-23 15:50:48
400	Matroid Secretary Problem in the Random Assignment Model Jose´ Soto Department of Mathematics M.I.T. Add to Reading List Source URL: www.dim.uchile.cl - Date: 2013-08-08 17:44:21

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