Learning to Predict Phases of Manipulation Tasks as Hidden States Oliver Kroemer, Herke van Hoof, Gerhard Neumann, and Jan Peters Abstract— Phase transitions in manipulation tasks often occur when contacts between obje

Source URL: www.ias.informatik.tu-darmstadt.de

• Hidden Markov model
• Markov chain
• Phase transition
• Kalman filter
• Expectation–maximization algorithm
• Stochastic matrix
• Robotics
• Markov models
• Statistics
• Probability and statistics

MAX SM MODEL ATTRIBUTE MATRIX

Source URL: www.mic.org

• Systems engineering process
• Decimal
• Numbers
• Data
• Information
• Data modeling
• EXPRESS
• Attribute

DOT MATRIX DRS MODEL UNITED NATIONS CONFERENCE 2014 Sl. No. Countries

Source URL: media.wix.com

Ruhr Graduate School in Economics University of Duisburg-Essen 10th Ruhr Graduate Summer School Essen, Germany

Source URL: www.iwb.wiwi.uni-due.de

• Computable general equilibrium
• Computer algebra systems
• Economic model
• General equilibrium theory
• GTAP
• Applied general equilibrium
• Macroeconomic model
• New Trade Theory
• Social accounting matrix
• Economics
• Economic theories
• Macroeconomics

Clustering by Local Skewering∗ David W. Scott Department of Statistics Rice University, Houston, Texas[removed]http://www.stat.rice.edu/∼scottdw March 31, 2005

Source URL: www.stat.rice.edu

• Singular value decomposition
• Covariance and correlation
• Statistical inference
• Maximum likelihood
• Principal component analysis
• Multivariate normal distribution
• Mixture model
• Expectation–maximization algorithm
• Covariance matrix
• Statistics
• Estimation theory
• Data analysis

Improve Latent Semantic Analysis based Language Model by Integrating Multiple Level Knowledge Rong Zhang and Alexander I. Rudnicky School of Computer Science, Carnegie Mellon University 5000 Forbes Avenue, Pittsburgh, PA

Source URL: www.cs.cmu.edu

• Artificial intelligence
• Statistical natural language processing
• Information retrieval
• Speech recognition
• Latent semantic analysis
• N-gram
• Semantic similarity
• Language model
• Document-term matrix
• Natural language processing
• Science
• Computational linguistics

A Bayesian Matrix Factorization Model for Relational Data Ajit P. Singh Department of Electrical Engineering University of Washington Seattle, WA 98195, USA

Source URL: www.cs.cmu.edu

• Statistical theory
• Monte Carlo methods
• Regression analysis
• Conjugate prior
• Metropolis–Hastings algorithm
• Generalized linear model
• Maximum likelihood
• Variational Bayesian methods
• Bayesian inference
• Statistics
• Bayesian statistics
• Estimation theory

A Bayesian Matrix Model for Relational Data Geoffrey J. Gordon Machine Learning Department Carnegie Mellon University Pittsburgh, PA 15213, USA

Source URL: www.cs.cmu.edu

• Statistical theory
• Markov chain Monte Carlo
• Multivariate statistics
• Conjugate prior
• Metropolis–Hastings algorithm
• Maximum likelihood
• Bayesian inference
• Generalized linear model
• Gibbs sampling
• Statistics
• Bayesian statistics
• Estimation theory

Online Spectral Identification of Dynamical Systems Geoff Gordon Machine Learning Department Carnegie Mellon University Pittsburgh, PA 15213

Source URL: www.cs.cmu.edu

• Matrix theory
• Markov models
• Hidden Markov model
• Kalman filter
• Singular value decomposition
• Matrix
• Dynamical system
• Predictive state representation
• Machine learning
• Algebra
• Mathematics
• Linear algebra

Using Web Co-occurrence Statistics for Improving Image Categorization Samy Bengio, Jeff Dean, Dumitru Erhan, Eugene Ie Quoc Le, Andrew Rabinovich, Jon Shlens, and Yoram Singer {bengio,jeff,dumitru,eugeneie}@google.com

Source URL: static.googleusercontent.com

• Computer vision
• Statistical models
• Confidence interval
• Econometrics
• Measurement
• Co-occurrence matrix
• Mixture model
• Object recognition
• Entailment
• Statistics
• Logic
• Image processing