Illinois Structured Learning Package v1.0.0

Illinois Structured Learning Package (Illinois-SL) is a general purpose JAVA library for performing structured learning. It houses learning algorithms like averaged Structured Perceptron and Structured SVM with L2-Loss, and provides a minimal interface for your structured learning needs. The training algorithm employed for training SSVM is dual coordinate descent(DCD), which has been proven to have very good convergence properties. Illinois-SL comes with an efficient implementation of DCD with support for multi-threading. Illinois-SL provides a simple and neat framework for developing applications using structured prediction models.

Maven Coordinates

To use Illinois-SL in your project add the following to your pom,

  <dependencies>
  ...  
    <dependency>
      <groupId>edu.illinois.cs.cogcomp</groupId>
      <artifactId>illinois-sl-core</artifactId>
      <version>1.0.0</version>
    </dependency>
  ...
  </dependencies>

<repositories>
  ...
    <repository>
      <id>CogcompSoftware</id>
      <name>CogcompSoftware</name>
      <url>http://cogcomp.cs.illinois.edu/m2repo/</url>
    </repository>
  ...  
  </repositories>

Example Usage

We provide detailed examples in an accompanying package at illinois-sl-examples.

License

The Illinois Structured Learning Package is available under a Research and Academic use license. For more details, view the license file LICENSE.

System requirements

The Illinois Structured Learning Package was developed on and for GNU/Linux, specifically CENTOS (2.6.18-238.12.1.el5) and Scientific Linux (2.6.32-279.5.2.el6.x86_64). There are no guarantees for running it under any other operating system, but we hope it should run on a Linux OS without any issues.

We assume that the package is installed on a machine with sufficient memory. The actual requirement of the memory depends on the task and size of the learning problem.

NOTE: When running your project, if working with a large dataset, you may need to invoke your project using the -Xmx1G and -XX:MaxPermSize=1G JVM command line parameters.

Additional Documentation/Citation

Additional documentation is available in the JavaDoc located in doc/index.html

Citing

Please cite the following papers when using this library

M.-W. Chang, V. Srikumar, D. Goldwasser and Dan Roth. Structured output learning with indirect supervision. ICML, 2010.

K.-W. Chang, V. Srikumar, D. Roth. Multi-core Structural SVM Training. ECML, 2013.

Contact Information

Please open a new issue with a minimal working example, in case you run into problems when using this package, and we will assist you. You can also email your questions to illinois-ml-nlp-users@cs.uiuc.edu.

kordjamshidi / illinois-sl