Replica Exchange for Non-Convex Optimization
Authors: Jing Dong, Xin T. Tong
JMLR 2021 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We further verify our theoretical results through some numerical experiments, and observe superior performance of the proposed algorithm over running GD or LD alone. In this section, we provide some numerical experiments to illustrate the performance of (n)GDx LD and (n)SGDx SGLD. |
| Researcher Affiliation | Academia | Jing Dong EMAIL Graduate School of Business Columbia University 3022 Broadway New York, NY 10027, USA Xin T. Tong EMAIL Department of Mathematics National University of Singapore Block S17, 10 Lower Kent Ridge Road Singapore 119077 |
| Pseudocode | Yes | Algorithm 1: GDx LD and n GDx LD: offline optimization... Algorithm 2: SGDx SGLD and n SGDx SGLD: online optimization |
| Open Source Code | No | The paper does not provide an explicit statement or a link to an open-source code repository for the described methodology. |
| Open Datasets | No | The paper describes the generation of data for its numerical experiments, such as 'Gaussian-mixture density' and 'mixture of Gaussian distribution', and uses mathematical test functions like 'Rastrigin function' and 'Griewank function'. It does not explicitly provide access information (links, DOIs, or citations) for any pre-existing public datasets. |
| Dataset Splits | No | The paper uses generated data and mathematical test functions and does not discuss specific training/test/validation dataset splits. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific software or library version numbers used for implementing the algorithms or conducting experiments. |
| Experiment Setup | Yes | We implement GDx LD for the objective function plotted in Figure 2 with h = 0.1, γ = 1, X0 = (0, 0), and Y0 = (1, 1). ... We set h = 0.1, γ = 1, Θ = 103, t0 = 0.05, Mv = 5, X0 = (0, 0), and Y0 = (1, 1). |