ABSTRACT

Rare category analysis refers to the problem of studying rare examples from the under-represented minority groups in an imbalanced data, which are observed in a variety of high-impact applications, such as fraud detection, emerging trend detection, rare disease diagnosis, and de-nov drug discovery. This tutorial aims to provide a concise review of the recent developments on rare category characterization, inference, and generalization in the data presented as graphs. In this tutorial, we will provide a concise review of rare category analysis on graph-structured data. In particular, we will start with the background and the unique challenges of rare category analysis on graphs, including (1) the highly-skewed class-membership distribution; (2) the non-separability nature of the rare categories from the majority classes; (3) the data and task heterogeneity, e.g., the multi-modal representation of examples, and the analysis of similar rare categories across multiple related tasks. Then we will introduce the recent developments in this problem setting, from representing rare patterns in a salient embedding space to the inference step that characterizes rare examples in a compact representation; from interpreting the prediction results to generating high-quality synthetic rare category examples for downstream applications, such as data augmentation and novelty discover. In the end, we will discuss the key challenges in rare category analysis and future directions.

Tutorial Slides

[PDF]

Outline

• Introduction (10 mins)

  • What is rare categories

  • What are the key challenges in rare category analysis

  • What are some real-world applications with respect to rare category analysis

• Part I: Rare Category Representation (20 mins)

  • Unsupervised representation learning

  • Supervised representation learning

• Part II: Rare Category Inference (20 mins)

  • Inferences for prediction

  • Inferences for interpretation

• Part III: Rare Category Generalization (30 mins)

  • Data augmentation

  • Novelty Discovery

• Part IV: An End-to-End Rare Category Analysis Prototype (5 mins)

• Part V: Conclusion and Future Directions (5 mins)

• Part VI: Q&A (5 mins)

Speakers