UCL Tutorial on: Deep Belief Nets (An updated and extended version of my 2007 NIPS tutorial) Geoffrey Hinton Canadian Institute for Advanced Research

Source URL: www.cs.toronto.edu

• Cybernetics
• Perceptron
• Nonlinear dimensionality reduction
• Backpropagation
• Statistical classification
• Generative model
• Types of artificial neural networks
• Feedforward neural network
• Neural networks
• Statistics
• Machine learning

Curriculum Vitae Michael S. Gashler Research Scientist Specializing in Machine Learning [removed[removed]day), [removed]eve)

Source URL: gashler.com

• Econometrics
• Network architecture
• Networks
• Neural network
• Institute of Electrical and Electronics Engineers
• Machine learning
• Waffles
• Nonlinear dimensionality reduction
• Dimension reduction
• Statistics
• Multivariate statistics
• Computational neuroscience

REPORTS Fig. 3. Theory, presented as the experiment (see Fig. 1). The SHG source is the magnetic component of the Lorentz force on metal electrons in the SRRs. The setup for measuring the SHG is described

Source URL: deeplearning.cs.cmu.edu

• Nonlinear dimensionality reduction
• Principal component analysis
• Dimension reduction
• Boltzmann machine
• Backpropagation
• Autoencoder
• Support vector machine
• Statistics
• Neural networks
• Multivariate statistics

Curriculum Vitae Michael S. Gashler, Ph.D. Assistant Professor Department of Computer Science and Computer Engineering University of Arkansas

Source URL: uaf46365.ddns.uark.edu

• Software optimization
• Waffles
• Computational neuroscience
• Cybernetics
• Nonlinear dimensionality reduction
• Neural network
• Supervised learning
• Transduction
• Algorithm
• Statistics
• Science
• Machine learning

Dimensionality Reduction: A Comparative Review L.J.P. van der Maaten ∗ , E.O. Postma, H.J. van den Herik MICC, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands. Abstract In recent years, a varie

Source URL: www.iai.uni-bonn.de

• Multivariate statistics
• Dimension reduction
• Machine learning
• Linear algebra
• Computational statistics
• Nonlinear dimensionality reduction
• Principal component analysis
• Kernel principal component analysis
• Semidefinite embedding
• Statistics
• Algebra
• Mathematics

A Cross-media Model for Automatic Image Annotation Lamberto Ballan∗, Tiberio Uricchio∗, Lorenzo Seidenari, and Alberto Del Bimbo Media Integration and Communication Center (MICC), Università degli Studi di Firenze V

Source URL: www.micc.unifi.it

• Statistics
• Multivariate statistics
• Search algorithms
• Dimension reduction
• Nonlinear dimensionality reduction
• K-nearest neighbor algorithm
• Automatic image annotation
• Content-based image retrieval
• Image retrieval
• Artificial intelligence
• Artificial intelligence applications
• Image search

Awards & Announcements Dr. Tong Zhang Machine Learning Methods for Big Data Analytics This project studies methods for scalable data analysis, including sampling methods, dimensionality reduction techniques as well as l

Source URL: stat.rutgers.edu

Knowledge Discovery with Iterative Denoising Kendall Giles

Source URL: www.people.vcu.edu

• Unsupervised learning
• Overfitting
• Dimension reduction
• Feature selection
• Curse of dimensionality
• Enron
• Machine learning
• Statistics
• Supervised learning

REPORTS 23; right 36, 13, and 27); superior frontal gyrus (left ⫺9, 31, and 45; right 17, 35, and 37).

Source URL: web.mit.edu

• Computational statistics
• Isomap
• Nonlinear dimensionality reduction
• Multidimensional scaling
• Principal component analysis
• Manifold
• Geodesic
• Differentiable manifold
• Topological manifold
• Statistics
• Multivariate statistics
• Dimension reduction

Parametric Embedding for Class Visualization Tomoharu Iwata Kazumi Saito

Source URL: web.mit.edu

• Functions and mappings
• Computational statistics
• Dimension reduction
• Statistical classification
• Isomap
• Nonlinear dimensionality reduction
• Supervised learning
• Embedding
• Naive Bayes classifier
• Mathematics
• Statistics
• Abstract algebra