DLP 2023: International Workshop on Deep Learning Practice for High-Dimensional Sparse Data with RecSys 2023 Suntec Convention Centre Singapore, Singapore, September 18-22, 2023 |
Conference website | https://dlp4rec.github.io/ |
Submission link | https://easychair.org/conferences/?conf=dlp2023 |
Submission deadline | August 3, 2023 |
In the increasingly digitalized world, recommender systems play a crucial role in processing, understanding, and leveraging vast amounts of data collected from the Internet. By accurately modeling user interests and intentions based on their behavioral data, recommender systems can substantially improve user experiences, drive user engagement, and ultimately boost revenue.
Recently, we have witnessed that deep learning-based approaches have been widely applied to empower recommender systems by better leveraging the massive data. However, the data utilized in recommender systems typically comprises a large volume of users, items, and user-generated tabular data, which is high-dimensional and extremely sparse. This contrasts with dense data processing applications, such as image classification and speech recognition, where deep learning-based approaches have been extensively explored. How to mine, model, and inference from such high-dimensional sparse data becomes an interesting problem. Furthermore, leveraging such data with deep learning techniques could be a new research direction with high practical value. The characteristics of such data pose unique challenges to the adoption of deep learning in these applications, including modeling, training, online serving, etc. As more academic and industry communities have initiated endeavors to address these challenges, this workshop will offer a platform for researchers and engineers to discuss and identify the obstacles, utilize the opportunities, and propose innovative ideas for the practical application of deep learning on high-dimensional sparse data.
Submission Guidelines
Submissions are limited to a total of 9 (nine) pages in a double-column format, including all content and references. Submissions must be in PDF format and formatted according to the latest ACM Conference Proceedings Template. Short papers are also welcomed. Reviews are not double-blind, and author names and affiliations should be listed
All submissions can be made through EasyChair using the following link: https://easychair.org/conferences/?conf=dlp2023
List of Topics
- Large-scale user response prediction modeling
- Representation learning for high-dimensional sparse data
- Embedding techniques, manifold learning, and dictionary learning
- User behavior understanding
- Large-scale recommendation and retrieval system
- Model compression for industrial application
- Scalable, distributed, and parallel training system for deep learning
- High throughput and low latency real-time serving system
- Applications of transfer learning, meta learning for sparse data
- Auto machine learning, auto feature selection
- Explainable deep learning for high-dimensional data
- Data augmentation, and anomaly detection for high-dimensional sparse data
- Generative adversarial network for sparse data
- Large language model-enhanced recommender systems
- Other challenges encountered in real-world applications
Contact
All questions about submissions should be emailed to dlp_2023@163.com.