Distributed Self-Paced Learning in Alternating Direction Method of Multipliers
Authors: Xuchao Zhang, Liang Zhao, Zhiqian Chen, Chang-Tien Lu
IJCAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments on both synthetic and real datasets demonstrate that our approach is superior to those of existing methods. and 5 Experimental Results |
| Researcher Affiliation | Academia | 1Discovery Analytics Center, Virginia Tech, Falls Church, VA, USA 2George Mason University, Fairfax, VA, USA |
| Pseudocode | Yes | Algorithm 1: DSPL ALGORITHM |
| Open Source Code | Yes | Details of both the source code and the datasets used in the experiment can be downloaded here3. 3https://goo.gl/cis7tK |
| Open Datasets | Yes | The real-world datasets utilized consisted of house rental transaction data from two cities, New York City and Los Angeles listed on the Airbnb4 website from January 2015 to October 2016. These datasets can be publicly downloaded5. ... 5http://insideairbnb.com/get-the-data.html |
| Dataset Splits | No | For the New York City dataset, the first 321,530 data samples from January 2015 to December 2015 were used as the training data and the remaining 329,187 samples from January to October 2016 as the test data. No explicit mention of a separate validation set was found. |
| Hardware Specification | Yes | All the experiments were performed on a 64bit machine with an Intel(R) Core(TM) quad-core processor (i7CPU@3.6GHz) and 32.0GB memory. |
| Software Dependencies | No | The paper does not mention specific version numbers for any software dependencies, such as programming languages, libraries, or frameworks used in the experiments. |
| Experiment Setup | Yes | The traditional self-paced learning algorithm (SPL) [Kumar et al., 2010] with the parameter λ = 1 and the step size µ = 1.1 was also compared in our experiment. For DSPL, we used the same settings as for SPL with the initial λ0 = 0.1 and τλ = 1. All the results from each of these comparison methods were averaged over 10 runs. |