Gradient Projection Iterative Sketch for Large-Scale Constrained Least-Squares
Authors: Junqi Tang, Mohammad Golbabaee, Mike E. Davies
ICML 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We demonstrate our methods computational efficiency compared to the classical accelerated gradient method, and the variance-reduced stochastic gradient methods through numerical experiments in various large synthetic/real data sets. |
| Researcher Affiliation | Academia | 1Institute for Digital Communications, the University of Edinburgh, Edinburgh, UK. Correspondence to: Junqi Tang <J.Tang@ed.ac.uk>. |
| Pseudocode | Yes | Algorithm 1 Gradient Projection Iterative Sketch G(m, [η], [k]) Algorithm 2 Accelerated Gradient Projection Iterative Sketch A(m, [η], [k]) Algorithm 3 line-search scheme for GPIS and Acc-GPIS L(xi, ft(x), ft(xi), γu, γd) |
| Open Source Code | No | The paper only provides a link to a third-party implementation (SAGA) for comparison, not the source code for their proposed GPIS/Acc-GPIS methods. |
| Open Datasets | Yes | We first run an unconstrained least-squares regression on the Year-prediction (Million-song) data set from UCI Machine Learning Repository (Lichman, 2013)... Then we choose Magic04 Gamma Telescope data set from (Lichman, 2013) |
| Dataset Splits | No | The paper mentions synthetic and real datasets but does not specify the splits (e.g., percentages, counts, or methodology) for training, validation, or testing. |
| Hardware Specification | Yes | We run all the numerical experiments on a DELL laptop with 2.60 GHz Intel Core i7-5600U CPU and 1.6 GB RAM, MATLAB version R2015b. |
| Software Dependencies | Yes | MATLAB version R2015b. |
| Experiment Setup | Yes | The sketch size of our proposed methods for each experiments are list in Table 1. We implement the line-search scheme given by (Nesterov, 2007) and is described by Algorithm 3 for GPIS and Acc-GPIS in our experiments with parameters γu = 2, and γd = 2. |