CanText: An exploration of dynamic reading experiences using context-specific media objects. Andrew McCallum Date of Submission

Source URL: deepview.cs.st-andrews.ac.uk

• Computing
• HTML
• Electronic engineering
• Design
• Communication design
• Web design
• Technical communication
• Reference
• Hypertext
• Multimedia
• Cascading Style Sheets
• Citation

Canonicalization of Database Records using Adaptive Similarity Measures Aron Culotta, Michael Wick, Robert Hall, Matthew Marzilli, Andrew McCallum Department of Computer Science University of Massachusetts Amherst, MA 01

Source URL: people.cs.umass.edu

Learning Field Compatibilities to Extract Database Records from Unstructured Text Michael Wick, Aron Culotta and Andrew McCallum Department of Computer Science University of Massachusetts Amherst, MA 01003

Source URL: people.cs.umass.edu

FACTORIE: Efficient Probabilistic Programming for Relational Factor Graphs via Imperative Declarations of Structure, Inference and Learning Andrew McCallum, Khashayar Rohanemanesh, Michael Wick, Karl Schultz, Sameer Sing

Source URL: ciir-publications.cs.umass.edu

SampleRank: Learning Preferences from Atomic Gradients Michael Wick, Khashayar Rohanimanesh, Aron Culotta∗, Andrew McCallum Department of Computer Science University of Massachusetts Amherst

Source URL: people.cs.umass.edu

Scalable Probabilistic Databases with Factor Graphs and MCMC Michael Wick Andrew McCallum

Source URL: people.cs.umass.edu

Community-based Link Prediction with Text David Mimno, Hanna Wallach, Andrew McCallum Department of Computer Science University of Massachusetts, Amherst Amherst, MA

Source URL: dirichlet.net

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

Advances in Learning and Inference for Partition-wise Models of Coreference Resolution Michael Wick and Andrew McCallum CMPSCI Technical Report UM-CS

Source URL: people.cs.umass.edu

Training Factor Graphs with Reinforcement Learning For Efficient MAP Inference Michael Wick, Khashayar Rohanimanesh, Sameer Singh, and Andrew McCallum University of Massachusetts Computer Science Department (IESL) Proba

Source URL: people.cs.umass.edu