Classification and Feature Selection on Matrix Data with Application to Gene-Expression Analysis Sepp Hochreiter Klaus Obermayer Fakult¨at f¨

Source URL: www.bioinf.jku.at

• Linear algebra
• Vectors
• Numerical linear algebra
• Statistical classification
• Support vector machine
• Euclidean vector
• Basis
• Kernel
• Vector space
• Isotope lists
• 73-96

Lecture 4: Modeling Sparse Matrix-Vector Multiply William Gropp www.cs.illinois.edu/~wgropp Sustained Memory Bandwidth

Source URL: wgropp.cs.illinois.edu

• Central processing unit
• Computer memory
• Cache
• Programming languages
• CPU cache
• Sparse matrix
• Processor register
• Fortran
• Data

LEARNING A FEATURE SPACE FOR SIMILARITY IN WORLD MUSIC Maria Panteli, Emmanouil Benetos, Simon Dixon Centre for Digital Music, Queen Mary University of London, United Kingdom {m.panteli, emmanouil.benetos, s.e.dixon}@qmu

Source URL: wp.nyu.edu

• Multivariate statistics
• Robust statistics
• Outlier
• K-nearest neighbors algorithm
• RANSAC
• Mahalanobis distance
• Non-negative matrix factorization
• Principal component analysis
• Linear discriminant analysis
• Music information retrieval
• Feature
• Data analysis

UNDERSTANDING TRANSFORMATIONS OF GEOGRAPHIC INFORMATION Nicholas Chrisman chrisman@u. washington.edu Department of Geography, University of Washington Seattle WA

Source URL: mapcontext.com

• Cartography
• Geography
• Image processing
• Geographic information system
• Contour line
• Linear interpolation
• Triangulation
• Level of measurement
• Image scaling
• Matrix
• Map
• Data transformation

1 Tensor Completion for Estimating Missing Values in Visual Data Ji Liu, Przemyslaw Musialski, Peter Wonka, and Jieping Ye Abstract—In this paper we propose an algorithm to estimate missing values in tensors of visual

Source URL: peterwonka.net

• Linear algebra
• Matrix theory
• Tensors
• Mathematical optimization
• Numerical linear algebra
• Matrix completion
• Tensor rank decomposition
• Low-rank approximation
• Singular value decomposition
• Matrix
• Tensor
• Semidefinite programming

From SIAM News, Volume 39, Number 8, OctoberBridging the Gap Between Numerical Linear Algebra, Theoretical Computer Science, and Data Applications By Gene H. Golub, Michael W. Mahoney, Petros Drineas, and Lek-Heng

Source URL: mmds-data.org

• Matrix theory
• Linear algebra
• Numerical linear algebra
• Multivariate statistics
• Multilinear algebra
• Higher-order singular value decomposition
• Non-negative matrix factorization
• Singular value decomposition
• Tensor
• Matrix
• Rank
• Orthogonal matrix

Locally-biased analytics You have BIG data and want to analyze a small part of it:

Source URL: mmds-data.org

• Matrix theory
• Linear algebra
• Singular value decomposition
• Abstract algebra
• Eigenvalues and eigenvectors
• Graph partition
• PageRank
• Image segmentation

We explore the trade-offs of performing linear algebra in Apache Spark versus the traditional C and MPI approach by examining three widely-used matrix factorizations: NMF (for physical plausibility), PCA (for its ubiquit

Source URL: mmds-data.org

Recommendation engines have a number of different applications. From books to movies, they enable the analysis and prediction of consumer preferences. The prevalence of recommender systems in both the business and comput

Source URL: mmds-data.org

• Recommender system
• Non-negative matrix factorization
• Nearest neighbor search

Text as Data Zoltan Fazekas zfazekas.github.io 19 November 2015 @cph ssd

Source URL: sebastianbarfort.github.io

• Natural language processing
• N-gram
• Document-term matrix
• Grimmer
• Matrix