THIS IS A DRAFT VERSION. FINAL VERSION TO BE PUBLISHED AT NIPS ’06 Structure Learning in Markov Random Fields Sridevi Parise Bren School of Information and Computer Science

Source URL: www.ics.uci.edu

• Probability theory
• Estimation theory
• Graphical models
• Marginal likelihood
• Expectation–maximization algorithm
• Variational Bayesian methods
• Normal distribution
• Maximum likelihood
• Bayesian network
• Statistics
• Bayesian statistics
• Statistical theory

Evidence Estimation for Bayesian Partially Observed MRFs Yutian Chen Department of Computer Science University of California, Irvine Irvine, CA 92697

Source URL: www.ics.uci.edu

• Normal distribution
• Expectation–maximization algorithm
• Variational Bayesian methods
• Bayesian network
• Markov chain Monte Carlo
• Maximum likelihood
• Deviance information criterion
• Pierre-Simon Laplace
• Markov random field
• Statistics
• Bayesian statistics
• Marginal likelihood

Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring Sungjin Ahn Dept. of Computer Science, UC Irvine, Irvine, CA, USA SUNGJIA @ ICS . UCI . EDU

Source URL: www.ics.uci.edu

• Fisher information
• Markov chain Monte Carlo
• Normal distribution
• Stochastic gradient descent
• Maximum a posteriori estimation
• Confidence interval
• Central limit theorem
• Score
• Expectation–maximization algorithm
• Statistics
• Estimation theory
• Maximum likelihood

Collapsed Variational Dirichlet Process Mixture Models∗ Max Welling Kenichi Kurihara Dept. of Computer Science Dept. of Computer Science UC Irvine, USA

Source URL: www.ics.uci.edu

• Expectation–maximization algorithm
• Dirichlet process
• Mixture model
• Latent Dirichlet allocation
• Normal distribution
• Factorial
• Markov chain
• Central limit theorem
• Bayesian inference
• Statistics
• Bayesian statistics
• Variational Bayesian methods

Typed Normal Form Bisimulation Soren B. Lassen1 and Paul Blain Levy2 1 2

Source URL: www.cs.bham.ac.uk

• Logic in computer science
• Lambda calculus
• Process calculi
• Π-calculus
• Bisimulation
• Combinatory logic
• Fixed-point combinator
• Sheaf
• Theoretical computer science
• Applied mathematics
• Mathematics

COMPUTER SCIENCE TRIPOS Part IB – 2013 – Paper 6 4 Computation Theory (AMP) (a) (i ) What does it mean for a λ-term to be a β-normal form? Defining the sets of canonical (C) and neutral (U ) λ-terms by the grammar

Source URL: www.cl.cam.ac.uk

BRICS Basic Research in Computer Science ´ BRICS RSEsik & Leiß: Greibach Normal Form in Algebraically Complete Semirings

Source URL: www.brics.dk

ALGORITHMIC CONSTRUCTION OF NORMAL MORSE DATA FOR SINGULARITIES ¨ OF COMPLEX ANALYTIC VARIETIES USING COMPREHENSIVE GROBNER BASES Yoshinao SHIRAKI Department of Information Science, Shonan Institute of Technology.

Source URL: ticsp.cs.tut.fi

Template for abstract preparation for the 21st PSI (Times font, 14pt, bold, centered) A. First, B. Second, C. Thirda (Times font, 12pt, normal, centered) National Institute for Fusion Science,322-6 Oroshi-cho, Toki 509-5

Source URL: psi2014.nifs.ac.jp

REGRET ANALYSIS OF A BANDIT PROBLEM FOR NORMAL DISTRIBUTIONS WITH UNKNOWN MEANS AND VARIANCES Junya Honda Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, The University of Tokyo. 5

Source URL: www.me.inf.kyushu-u.ac.jp