Fast inference in generalized linear models via expected log-likelihoods Alexandro D. Ramirez 1,*, Liam Paninski 2 1 Weill Cornell Medical College, NY. NY, U.S.A *

Source URL: www.stat.columbia.edu

• Estimation theory
• Statistical theory
• Maximum likelihood estimation
• Bias of an estimator
• Completeness
• Poisson regression
• Linear regression
• Exponential family
• Likelihood function
• Estimator
• Mean squared error
• Law of large numbers

CAUTION: This is an exam from a different semester. The subject matter was comparable, but the text, the audience, the instructor, and the testing environment may have been different from what you will face. Please remem

Source URL: www.math.niu.edu

• Logarithms
• Functions and mappings
• Mathematical analysis
• Differential calculus
• E
• Natural logarithm
• Derivative
• Integral
• Lambert W function
• Exponential family

PU-BCD: Exponential Family Models for the Coarse- and Fine-Grained All-Words Tasks Jonathan Chang Miroslav Dud´ık, David M. Blei Princeton University Princeton University

Source URL: wordnet.cs.princeton.edu

• Computational linguistics
• Natural language processing
• Semantics
• Lexical semantics
• Word-sense disambiguation
• WordNet
• SemEval
• Model theory

Fitting Power Law Distributions to Data Willy Lai Introduction In this paper, we will be testing whether the frequency of family names from the 2000 Census follow a power law distribution. Power law distributions are usu

Source URL: www.stat.berkeley.edu

• Probability distributions
• Hypothesis testing
• Statistical tests
• Design of experiments
• Statistical inference
• Normal distribution
• Exponential distribution
• Likelihood-ratio test
• Statistical hypothesis testing
• KolmogorovSmirnov test
• Log-normal distribution
• Statistical power

Learning with Marginalized Corrupted Features Laurens van der Maaten Delft University of Technology, Mekelweg 4, 2628 CD Delft, THE NETHERLANDS Minmin Chen

Source URL: lvdmaaten.github.io

• Statistical classification
• Probability distributions
• Exponentials
• Machine learning
• Linear classifier
• Pattern recognition
• Support vector machine
• Deep learning
• Natural exponential family
• Poisson distribution
• Normal distribution
• Loss function

1 Event-based, 6-DOF Camera Tracking for High-Speed Applications Abstract—In contrast to standard cameras, which produce frames at a fixed rate, event cameras respond asynchronously to pixel-level brightness changes,

Source URL: rpg.ifi.uzh.ch

• Robot control
• Computer animation
• Computer vision
• Probability distributions
• Exponentials
• Exponential family
• Kalman filter
• Pose
• Normal distribution
• Variational Bayesian methods
• Motion capture
• Mixture model

Models of Insurance Claim Counts with Time Dependence Based on Generalization of Poisson and Negative Binomial Distributions by Jean-Philippe Boucher, Michel Denuit, and Montserrat Guillén

Source URL: www.variancejournal.org

• Probability distributions
• Poisson distribution
• Generalized linear model
• Normal distribution
• Exponential family
• Negative binomial distribution
• Poisson regression
• Overdispersion
• Variance
• Compound Poisson distribution
• Mixed logit

Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures Mario Lucic† ETH Zurich

Source URL: jmlr.org

A Sufficient Statistics Construction of Exponential Family L´ evy Measure Densities for Nonparametric Conjugate Models: Supplementary Materail Proof of Lemma 1: The result in Lemma 1 follows from the definition of

Source URL: jmlr.org

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