Parallel Pareto Optimization for Subset Selection
Authors: Chao Qian, Jing-Cheng Shi, Yang Yu, Ke Tang, Zhi-Hua Zhou
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Empirical studies verify the effectiveness of PPOSS, and moreover suggest that the asynchronous implementation is more efficient with little quality loss. |
| Researcher Affiliation | Academia | 1National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China 2UBRI, School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China |
| Pseudocode | Yes | Algorithm 1 POSS Algorithm 2 Parallel POSS (PPOSS) |
| Open Source Code | No | The paper does not provide a specific repository link, an explicit code release statement, or indicate code availability in supplementary materials for the methodology described. |
| Open Datasets | Yes | The data sets are from http://archive.ics.uci.edu/ml/ and http://www.csie.ntu.edu.tw/ cjlin/libsvmtools/datasets/. |
| Dataset Splits | No | The paper mentions using 6 datasets but does not provide specific dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) needed to reproduce the data partitioning for training, validation, and testing. |
| Hardware Specification | Yes | All of the experiments are coded in Java and run on an identical configuration: a server with 4 Intel(R) Xeon(R) CPU E5-2640 v2 (8 real cores each, 20M Cache, 2.00GHz, hyper-threading) and 32GB of RAM. The kernel is Linux 2.6.18-194.el5. |
| Software Dependencies | No | The paper states that experiments are 'coded in Java' and mentions 'Linux 2.6.18-194.el5' for the kernel, but it does not provide specific ancillary software details, such as Java version or specific library names with version numbers, needed to replicate the experiment. |
| Experiment Setup | Yes | We set the sparsity k = 8, and for PPOSS, we use the setting suggested by Theorem 1: T = b2ek2n/Nc. We test the number of cores N from 1 to 10. |