Call for Papers: 4th International Workshop on Deep Learning Practice for High‑Dimensional Sparse Data (DLP‑KDD 2022)

The 4th International Workshop on Deep Learning Practice for High‑Dimensional Sparse and Imbalanced Data (DLP‑KDD 2022) is announced, with a paper submission deadline of May 26, 2022 (extendable) and acceptance notifications on June 20, 2022.

Workshop website: https://dlp-kdd2022.github.io/ . Papers should be submitted via https://cmt3.research.microsoft.com/DLPKDD2022/ . Submissions may be up to 9 pages for long papers or 2–4 pages for short papers.

The workshop aims to explore deep‑learning applications on large‑scale industrial sparse data, addressing challenges such as over‑fitting, model redundancy, interpretability, and computational constraints.

1. Deep‑Learning System Construction and Optimization

Large Scale Recommendation and Retrieval System

High‑throughput and Low‑latency Real‑time Serving System

Scalable, Distributed and Parallel Training System for Deep Learning

Auto Machine Learning

Auto Feature Selection

2. Data Representation and Mining

Representation Learning for High‑dimensional Sparse Data

Embedding Techniques and Large‑scale Pre‑training

Manifold Learning and Dictionary Learning

Applications of Transfer Learning

Meta Learning for Sparse Data

Explainable Deep Learning for High‑dimensional Data

Data Augmentation and Privacy Computing

Anomaly Detection for High‑dimensional Sparse Data

Generative Adversarial Networks for Sparse Data

3. User Modeling

Large Scale User Response Prediction Modeling

User Behavior Understanding

User Interest Mining

Other topics related to deep‑learning challenges and experiences in industrial practice are also welcome. The workshop invites contributions from both academia and industry.