<--- Back to Details
First PageDocument Content
Statistical theory / Estimation theory / XC / KullbackLeibler divergence / Cross entropy / Clique / Maximum likelihood estimation
Date: 2009-10-06 18:57:16
Statistical theory
Estimation theory
XC
KullbackLeibler divergence
Cross entropy
Clique
Maximum likelihood estimation

Which cliques? • In general, an undirected model can place potentials on any subset of the cliques of the graph. Lecture 11: Iterative Proportional Fitting

Add to Reading List

Source URL: www.cs.nyu.edu

Download Document from Source Website

File Size: 53,09 KB

Share Document on Facebook

Similar Documents

Cross-diffusion systems with entropy structure Ansgar J¨ ungel (TU Vienna) Cross-diffusion systems describe the diffusive interaction of multi-species systems. Examples include multi-species population dynamics, cell bi

Cross-diffusion systems with entropy structure Ansgar J¨ ungel (TU Vienna) Cross-diffusion systems describe the diffusive interaction of multi-species systems. Examples include multi-species population dynamics, cell bi

DocID: 1uigJ - View Document

Multifidelity preconditioning of the cross-entropy method for rare event simulation and failure probability estimation

Multifidelity preconditioning of the cross-entropy method for rare event simulation and failure probability estimation

DocID: 1tGD9 - View Document

Motivations  PRNG Security Model Java SecureRandom Analysis

Motivations PRNG Security Model Java SecureRandom Analysis

DocID: 1rmDv - View Document

PDF Document

DocID: 1r2P8 - View Document

Finding Progression Stages in Time-evolving Event Sequences Jaewon Yang†∗ Julian McAuley† Jure Leskovec† Paea LePendu‡ Nigam Shah‡ † Computer Science, Stanford University, {jayang, jmcauley, jure}@cs.stanfo

Finding Progression Stages in Time-evolving Event Sequences Jaewon Yang†∗ Julian McAuley† Jure Leskovec† Paea LePendu‡ Nigam Shah‡ † Computer Science, Stanford University, {jayang, jmcauley, jure}@cs.stanfo

DocID: 1qo0s - View Document