Original version appeared in the 15th International Symposium on Principles and Practice of Declarative Programming (PPDPEngineering Definitional Interpreters (Extended Version) Jan Midtgaard Norman Ramsey

Source URL: www.cs.tufts.edu

• Logic in computer science
• Greek letters
• Denotational semantics
• Eval
• Lua
• Normal distribution
• San
• Semantics

Gibbs Sampling for Logistic Normal Topic Models with Graph-Based Priors David Mimno, Hanna M. Wallach, Andrew McCallum Department of Computer Science University of Massachusetts

Source URL: dirichlet.net

Fast Randomized Kernel Ridge Regression with Statistical Guarantees∗ Ahmed El Alaoui † Michael W. Mahoney ‡ † Electrical Engineering and Computer Sciences ‡ Statistics and International Computer Science Institu

Source URL: www.stat.berkeley.edu

• Algebra
• Linear algebra
• Mathematics
• Matrix theory
• Numerical linear algebra
• Functional analysis
• Mathematical physics
• Normal distribution
• Low-rank approximation
• Eigendecomposition of a matrix
• Eigenvalues and eigenvectors
• Matrix

CS 532: Homework Assignment 6 Due: December 2, 6:00pm Philippos Mordohai Department of Computer Science Stevens Institute of Technology

Source URL: www.cs.stevens.edu

• 3D computer graphics
• 3D printing
• PLY
• Computer graphics
• Vertex
• Normal

Reprinted from the 15th International Symposium on Principles and Practice of Declarative Programming (PPDPEngineering Definitional Interpreters Jan Midtgaard Norman Ramsey

Source URL: www.cs.tufts.edu

• Computing
• Software engineering
• Software
• Greek letters
• Denotational semantics
• Logic in computer science
• Lua
• Normal distribution
• San
• String

An Academic Response to Basel 3.5 Paul Embrechts1 , Giovanni Puccetti2 , Ludger Rüschendorf3 , Ruodu Wang4 , and Antonela Beleraj2 1 RiskLab and SFI, Department of Mathematics, ETH Zurich, 8092 Zurich, Switzerland 2

Source URL: sas.uwaterloo.ca

• Probability
• Statistics
• Mathematical analysis
• Actuarial science
• Financial risk
• Mathematical finance
• Probability distributions
• Expected shortfall
• Value at risk
• Risk
• Expected value
• Normal distribution

Kernel Belief Propagation 1 Le Song,1 Arthur Gretton,1,2 Danny Bickson,1 Yucheng Low,1 Carlos Guestrin1 School of Computer Science, CMU; 2 Gatsby Computational Neuroscience Unit & MPI for Biological Cybernetics

Source URL: select.cs.cmu.edu

• Statistics
• Probability
• Mathematical analysis
• Machine learning
• Hilbert space
• Graphical models
• Probability theory
• Belief propagation
• Coding theory
• Positive-definite kernel
• Mixture model
• Normal distribution

Efficient Learning Strategy of Chinese Characters Based on Network Approach Xiaoyong Yan1,2, Ying Fan1, Zengru Di1, Shlomo Havlin3, Jinshan Wu1* 1 School of Systems Science, Beijing Normal University, Beijing, China, 2 C

Source URL: havlin.biu.ac.il

PARAMETER ESTIMATION IN TOTAL VARIATION BLIND DECONVOLUTION S. Derin Babacan1 , Rafael Molina2 , Aggelos K. Katsaggelos1 1 Department of Electrical Engineering and Computer Science

Source URL: decsai.ugr.es

• Statistics
• Mathematical analysis
• Probability
• Probability distributions
• Image processing
• Infinitely divisible probability distributions
• Bayesian statistics
• Signal processing
• Gamma distribution
• Normal distribution
• Deconvolution
• Convolution

Solving Heads-up Limit Texas Hold’em Oskari Tammelin,1 Neil Burch,2 Michael Johanson2 and Michael Bowling2 1 http://jeskola.net, 2 Department of Computing Science, University of Alberta

Source URL: poker.cs.ualberta.ca

• Mathematics
• Statistics
• Mathematical analysis
• Game theory
• Nash equilibrium
• Normal distribution
• Minimax