Distributed Distributionally Robust Optimization with Non-Convex Objectives
Authors: Yang Jiao, Kai Yang, Dongjin Song
NeurIPS 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive empirical studies on real-world datasets demonstrate that the proposed method can not only achieve fast convergence, and remain robust against data heterogeneity as well as malicious attacks, but also tradeoff robustness with performance. |
| Researcher Affiliation | Academia | Yang Jiao Tongji University yangjiao@tongji.edu.cn Kai Yang Tongji University kaiyang@tongji.edu.cn Dongjin Song University of Connecticut dongjin.song@uconn.edu |
| Pseudocode | Yes | Algorithm 1 ASPIRE-EASE |
| Open Source Code | No | The paper states 'The references of the data used in this paper are added in Section 6.1.' in response to a question about code, data, and instructions needed to reproduce results, but it does not provide an explicit statement about the release of its source code or a direct link to a repository. |
| Open Datasets | Yes | We compare the proposed ASPIRE-EASE with baseline methods based on SHL [20], Person Activity [26], Single Chest-Mounted Accelerometer (SM-AC) [9] and Fashion MNIST [51] datasets. |
| Dataset Splits | No | The paper refers to 'Section C.2' for data splits and training details in the ethics statement, but these details are not provided within the main body of the paper. |
| Hardware Specification | Yes | We implement our model with Py Torch and conduct all the experiments on a server with two TITAN V GPUs. |
| Software Dependencies | No | The paper mentions 'We implement our model with Py Torch' but does not specify the version number for PyTorch or any other software dependencies. |
| Experiment Setup | No | The paper states 'The base models are trained with SGD. More details are given in Appendix C.' which implies specific hyperparameters are deferred to the appendix and not present in the main text. |