GP-GPIS-OPT: Grasp Planning With Shape Uncertainty Using Gaussian Process Implicit Surfaces and Sequential Convex Programming Jeffrey Mahler1 , Sachin Patil1 , Ben Kehoe2 , Jur van den Berg3 , Matei Ciocarlie4 , Pieter A

Source URL: goldberg.berkeley.edu

• Statistics
• Probability
• Statistical theory
• Child development
• Grasp
• Normal distribution
• Gaussian process

Cumulative Probabilities for the Standard Normal (Z) Distribution Values in the table correspond to the area under the curve of a standard normal random variable for a value at or below z .

Source URL: www.sjsu.edu

CONFIDENTIAL. Limited circulation. For review only. Tumor Localization using Automated Palpation with Gaussian Process Adaptive Sampling Animesh Garg1,2 , Siddarth Sen2 , Rishi Kapadia2 , Yiming Jen2 , Stephen McKinley3

Source URL: goldberg.berkeley.edu

• Medical imaging
• Signal processing
• Palpation
• Physical examination
• Elastography
• Image segmentation
• Normal distribution
• Gaussian process
• Estimation theory
• Magnetic resonance elastography
• Haptic technology
• Variance

A Level-set Hit-and-run Sampler for Quasi-Concave Distributions Shane T. Jensen and Dean P. Foster Department of Statistics, The Wharton School, University of Pennsylvania Abstract

Source URL: www-stat.wharton.upenn.edu

• Monte Carlo methods
• Markov chain Monte Carlo
• Non-uniform random numbers
• Probability distributions
• Computational statistics
• Gibbs sampling
• Rejection sampling
• MetropolisHastings algorithm
• Slice sampling
• Bayesian network
• Quasiconvex function
• Normal distribution

AN ASYMPTOTIC FORMULA FOR THE NUMBER OF NON-NEGATIVE INTEGER MATRICES WITH PRESCRIBED ROW AND COLUMN SUMS Alexander Barvinok and J.A. Hartigan March 2011

Source URL: www.math.lsa.umich.edu

• Mathematics
• Algebra
• Mathematical analysis
• Matrix theory
• Linear algebra
• Normal distribution
• Determinant
• Matrix
• Central limit theorem
• Random permutation statistics
• Matrix exponential

Administrative Notes StatisticsLecture 20 •  Homework 6 is due in recitation on Friday, April 8th

Source URL: www-stat.wharton.upenn.edu

• Statistics
• Statistical theory
• Statistical inference
• Hypothesis testing
• Design of experiments
• Measurement
• Normal distribution
• Confidence interval
• Statistical hypothesis testing
• Population proportion
• Standard error
• P-value

On the concentration of expectation and approximate inference in layered networks Michael I. Jordan University of California Berkeley, CA 94720

Source URL: dept.stat.lsa.umich.edu

• Graphical models
• Probability distributions
• Bayesian network
• Networks
• Normal distribution
• Variational Bayesian methods
• Belief propagation
• Exponential family

Convergence of path measures arising from a mean field or polaron type interaction? Erwin Bolthausen1 , Jean-Dominique Deuschel2 , and Uwe Schmock1 1 2

Source URL: www.fam.tuwien.ac.at

• Mathematical analysis
• Probability
• Statistics
• Normal distribution
• Operator theory
• Mixing
• Distribution
• Polar coordinate system
• Symbol

Journal of Statistical Planning and Inference – 293 www.elsevier.com/locate/jspi Adaptive paired comparison design

Source URL: www-stat.wharton.upenn.edu

• Statistics
• Probability
• Statistical theory
• Bayesian statistics
• Regression analysis
• Swiss-system tournament
• Operations research
• Normal distribution
• Prior probability
• Optimal design
• Probability distribution

Iterative Maximum Likelihood on Networks Elchanan Mossel∗ and Omer Tamuz† arXiv:0904.4903v2 [math.ST] 4 MayMay 4, 2009

Source URL: people.hss.caltech.edu

• Estimation theory
• Statistical theory
• Estimator
• Bias of an estimator
• Variance
• Efficient estimator
• Minimum-variance unbiased estimator
• Efficiency
• Normal distribution
• Maximum likelihood estimation
• Consistent estimator
• Generalized least squares