Adding vs. Averaging in Distributed Primal-Dual Optimization
Authors: Chenxin Ma, Virginia Smith, Martin Jaggi, Michael Jordan, Peter Richtarik, Martin Takac
ICML 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We provide a thorough experimental comparison with competing algorithms using several real-world distributed datasets. Our practical results confirm the strong scaling of COCOA+ as the number of machines K grows, while competing methods, including the original COCOA, slow down significantly with larger K. We implement all algorithms in Spark, and our code is publicly available at: github.com/gingsmith/cocoa. |
| Researcher Affiliation | Academia | Chenxin Ma CHM514@LEHIGH.EDU Industrial and Systems Engineering, Lehigh University, USA Virginia Smith VSMITH@BERKELEY.EDU University of California, Berkeley, USA Martin Jaggi JAGGI@INF.ETHZ.CH ETH Z urich, Switzerland Michael I. Jordan JORDAN@CS.BERKELEY.EDU University of California, Berkeley, USA Peter Richt arik PETER.RICHTARIK@ED.AC.UK School of Mathematics, University of Edinburgh, UK Martin Tak aˇc TAKAC.MT@GMAIL.COM Industrial and Systems Engineering, Lehigh University, USA |
| Pseudocode | Yes | Algorithm 1 COCOA+ Framework |
| Open Source Code | Yes | We implement all algorithms in Spark, and our code is publicly available at: github.com/gingsmith/cocoa. |
| Open Datasets | Yes | The used datasets are summarized in Table 2. |
| Dataset Splits | No | The paper does not provide specific dataset split information (percentages, sample counts, or explicit splitting methodology) for training, validation, or test sets. |
| Hardware Specification | Yes | We implement all algorithms in Apache Spark (Zaharia et al., 2012) and run them on m3.large Amazon EC2 instances |
| Software Dependencies | No | The paper mentions 'Apache Spark' but does not specify its version number or any other software dependencies with their versions. |
| Experiment Setup | Yes | We compare the COCOA+ and COCOA frameworks directly using two datasets (Covertype and RCV1) across various values of λ, the regularizer, in Figure 1. For each value of λ we consider both methods with different values of H, the number of local iterations performed before communicating to the master. For all runs of COCOA+ we use the safe upper bound of γK for σ . |