Name
Title | ||
|---|---|---|
4th Workshop on Deep Learning Practice and Theory for High-Dimensional Sparse and Imbalanced Data with KDD 2022 |
Abstract | ||
|---|---|---|
Recently, we have witnessed that deep learning-based approaches have been widely applied. Particularly, some applications involve data that are high dimensional, sparse or imbalanced, which are different from those applications with dense data processing, such as image classification and speech recognition, where deep learning-based approaches have been extensively studied. One of the main applications is the user-centric platform that consists of great deal of users, items and user generated tabular data which are quite high-dimensional. The characteristics of such data pose unique challenges to the adoption of deep learning in these applications, including modeling, training, and online serving, etc. More and more communities from both academia and industry have initiated the endeavors to solve these challenges. This workshop will provide a venue for both the research and engineering communities to discuss and formulate the challenges, utilize opportunities, and propose new ideas in the practice and theory of deep learning on high-dimensional, sparse and imbalanced data. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1145/3534678.3542896 | KDD '22: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 13 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roberto Corizzo | 1 | 1 | 0.69 |
| Junfeng Ge | 2 | 0 | 0.34 |
| Colin Bellinger | 3 | 50 | 9.55 |
| Xiaoqiang Zhu | 4 | 0 | 0.34 |
| Paula Branco | 5 | 0 | 0.34 |
| Kuang-chih Lee | 6 | 0 | 0.34 |
| Nathalie Japkowicz | 7 | 2581 | 182.43 |
| Ruiming Tang | 8 | 125 | 19.25 |
| Tao Zhuang | 9 | 0 | 0.34 |
| Han Zhu | 10 | 215 | 8.48 |
| Bi-Ye Jiang | 11 | 163 | 7.00 |
| Jiaxin Mao | 12 | 164 | 26.30 |
| Weinan Zhang | 13 | 1228 | 97.24 |