Communication-Optimal Distributed Clustering
Authors: Jiecao Chen, He Sun, David Woodruff, Qin Zhang
NeurIPS 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We implement our algorithms and demonstrate this phenomenon on real life datasets, showing that our algorithms are also very efficient in practice. 5 Experiments In this section we present experimental results for spectral graph clustering in the message passing and blackboard models. |
| Researcher Affiliation | Collaboration | Jiecao Chen Indiana University Bloomington, IN 47401 jiecchen@indiana.edu He Sun University of Bristol Bristol, BS8 1UB, UK h.sun@bristol.ac.uk David P. Woodruff IBM Research Almaden San Jose, CA 95120 dpwoodru@us.ibm.com Qin Zhang Indiana University Bloomington, IN 47401 qzhangcs@indiana.edu |
| Pseudocode | No | The paper describes algorithms in prose and mathematical expressions but does not include structured pseudocode blocks. |
| Open Source Code | No | The paper does not provide any explicit statements or links indicating that the source code for their described methodology is openly available. |
| Open Datasets | No | The paper describes the datasets (Twomoons, Gauss, Sculpture) in detail, but it does not provide specific links, DOIs, or citations with author/year information for public access to these datasets. |
| Dataset Splits | No | The paper describes the datasets used but does not specify training, validation, or test splits by percentage or absolute counts, nor does it refer to standard predefined splits. |
| Hardware Specification | Yes | Our experiments were conducted on an IBM Ne Xt Scale nx360 M4 server, which is equipped with 2 Intel Xeon E5-2652 v2 8-core processors, 32GB RAM and 250GB local storage. |
| Software Dependencies | No | We implemented the algorithms using multiple languages, including Matlab, Python and C++. The paper lists programming languages but does not provide specific version numbers for any software dependencies, libraries, or solvers. |
| Experiment Setup | Yes | We implemented the algorithms using multiple languages, including Matlab, Python and C++. Our experiments were conducted on an IBM Ne Xt Scale nx360 M4 server, which is equipped with 2 Intel Xeon E5-2652 v2 8-core processors, 32GB RAM and 250GB local storage. In the message passing model each site samples 5n edges; in the blackboard model all sites jointly sample 10n edges and the chain has length 18. |