Online Learning from Capricious Data Streams: A Generative Approach
Authors: Yi He, Baijun Wu, Di Wu, Ege Beyazit, Sheng Chen, Xindong Wu
IJCAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The experimental results demonstrate that OCDS achieves conspicuous performance on both synthetic and real datasets. and 6 Experiments We use 15 UCI datasets [Dua and Karra Taniskidou, 2017] and 1 real-world IMDB dataset [Maas et al., 2011] to evaluate the performance of OCDS. |
| Researcher Affiliation | Academia | 1School of Computing and Informatics, University of Louisiana at Lafayette, USA 2Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, China |
| Pseudocode | Yes | Algorithm 1: Retrieval Strategy and Algorithm 2: The OCDS algorithm |
| Open Source Code | No | The paper does not include an explicit statement about releasing source code for the described methodology or a link to a code repository. |
| Open Datasets | Yes | We use 15 UCI datasets [Dua and Karra Taniskidou, 2017] and 1 real-world IMDB dataset [Maas et al., 2011] to evaluate the performance of OCDS. |
| Dataset Splits | No | The paper does not provide explicit details about training, validation, or test dataset splits (e.g., percentages, sample counts, or specific pre-defined splits). |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory) used for running the experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies or library versions used for the experiments. |
| Experiment Setup | Yes | To find the best settings of the parameters α, β1 and β2, we use grid searches ranging from 10 5 to 1. For memory and running time efficiency, we let |Ut| 150 by setting γ in different datasets. ... The ratio of the maximal removed features is denoted as VI . For example, VI = 0.5 means that at most 50% of features in xt are randomly removed. The default value of VI is 0.5 in our experiments. |