Structural Maxent Models
Authors: Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri, Umar Syed
ICML 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | report the results of several experiments demonstrating that its performance improves on that of existing L1-norm regularized Maxent algorithms. In Section 4, we report the results of extensive experiments with data from various domains including community crimes, traffic and species habitat modeling. |
| Researcher Affiliation | Collaboration | Corinna Cortes CORINNA@GOOGLE.COM Google Research, 111 8th Avenue, New York, NY 10011 Vitaly Kuznetsov VITALY@CIMS.NYU.EDU Courant Institute of Mathematical Sciences, 251 Mercer Street, New York, NY 10012 Mehryar Mohri MOHRI@CIMS.NYU.EDU Courant Institute and Google Research, 251 Mercer Street, New York, NY 10012 Umar Syed USYED@GOOGLE.COM Google Research, 111 8th Avenue, New York, NY 10011 |
| Pseudocode | Yes | Figure 1. Pseudocode of the Struct Maxent2 algorithm. |
| Open Source Code | No | We have fully implemented both Struct Maxent1 and Struct Maxent2 with diverse feature families and will make the software used in our experiments available as open-source. |
| Open Datasets | Yes | For our experiments, we used two data sets from (Phillips et al., 2006) which are accessible from http://www.cs.princeton.edu/ schapire/maxent. We also experimented with a Minnesota traffic dataset (Kwon, 2004) which is accessible from http://www.d.umn.edu/ tkwon/TMCdata/TMCarchive.html. We used the UCI Communities and Crime dataset as another test case for Struct Maxent algorithm. |
| Dataset Splits | Yes | For each species, we first randomly split the sample S into a training set S1 (70%) and a test set S2 (30%). We trained all algorithms on S1 and used the error on S2 to find the optimal value of the parameters λ and β. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory) used for running its experiments. |
| Software Dependencies | No | The paper states that software was implemented but does not provide specific ancillary software details (e.g., library or solver names with version numbers). |
| Experiment Setup | Yes | Specifically, we optimized over λ, β {0.0001, 0.001, 0.01, 0.1, 0.5, 1, 2}. We compared Struct Maxent with L1-regularized Maxent...we ran each algorithm for 500 rounds, or until the change in the objective on a single round fell below 10^-5. |