Perturb-and-MAP Random Fields: Using Discrete Optimization to Learn and Sample from Energy Models George Papandreou1 and Alan L. Yuille1,2 Department of Statistics, University of California, Los Angeles 2 Department of B

Source URL: www.stat.ucla.edu

• Statistical inference
• Probability theory
• Bayesian statistics
• Markov random field
• Maximum likelihood
• Gumbel distribution
• Expectation–maximization algorithm
• Perturbation theory
• Kullback–Leibler divergence
• Statistics
• Estimation theory
• Statistical theory

Objectively assessing geological maps using machine learning Matt Cracknell, Anya Reading & Andrew McNeill Cracknell, Reading & McNeill, 2014, Mapping geology and volcanic-hosted massive sulphide alteration in the Hellye

Source URL: www.tasmanianmining.com.au

• Scientific modeling
• Economic geology
• Geologic map
• Geomorphology
• Geologic modelling
• Random forest
• Machine learning
• Geology
• Science

SHAFIQUL ISLAM, University of Lethbridge Approximation of absolutely continious invariant measures for random dynamical systems A random map is a discrete-time dynamical system in which one of a number of transformations

Source URL: cms.math.ca

TN248 Mapping Battery-Backed SRAM When Running in Flash This document explains how to map battery-backed SRAM when using the BIOS memory setting “Code and BIOS in Flash” on boards that have both fast non battery-back

Source URL: ftp1.digi.com

• C POSIX library
• Computer memory
• C programming language
• C Standard Library
• Printf format string
• Sizeof
• Stat
• INT
• Random-access memory
• Computing
• Computer programming
• Computer architecture

Can a Forest/Nonforest Change Map Improve the Precision of Forest Area, Volume, Growth, Removals, and Mortality Estimates? Dale D. Gormanson, Mark H. Hansen, and Ronald E. McRoberts1 Abstract.—In an extensive forest in

Source URL: www.nrs.fs.fed.us

• Stratification
• Sample size determination
• Forest inventory
• Forest
• Random sample
• Statistics
• Sampling
• Stratified sampling

Quadratic Programming Relaxations for Metric Labeling and Markov Random Field MAP Estimation Pradeep Ravikumar John Lafferty School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA

Source URL: www.cs.cmu.edu

• Linear programming
• Convex optimization
• Linear programming relaxation
• Relaxation
• Quadratic programming
• Randomized rounding
• Duality
• Dynamic programming
• Mathematical optimization
• Operations research
• Mathematics

SOCNAV Degree Map Colleges of DCCCD/Dallas Colleges Online Associate in Arts General Education/ Undergraduate Transfer Degree Objective - In order to be eligible to receive this degree, a student must: Complete a minimum

Source URL: dlncpace.com

• Computer memory
• Dynamic random-access memory

SOCNAV Degree Map Colleges of DCCCD/Dallas Colleges Online Associate in Science General Education/ Undergraduate Transfer Degree Objective - In order to be eligible to receive this degree, a student must: Complete a mini

Source URL: dlncpace.com

• Computer memory
• Dynamic random-access memory

MAP Estimation, Message Passing, and Perfect Graphs Tony Jebara Columbia University New York, NY[removed]removed]

Source URL: www.cs.columbia.edu

• Graphical models
• Probability theory
• Line graph
• Clique
• Chordal graph
• Graph coloring
• Tree decomposition
• Perfect graph
• Markov random field
• Graph theory
• Graph operations
• NP-complete problems

Exploring Bright Fireballs on Earth Data gathered by U.S. government sensors between 1994 and 2013 shows that fireballs (called bolides by astronomers) are frequent and random as the map above shows. Over this 20-year i

Source URL: spacemath.gsfc.nasa.gov

• Measurement
• Energy
• Joule
• Impact event
• Kinetic energy
• Moon
• Meteoroid
• Physics
• Introductory physics
• Astronomy