← Search

Mingjia Yin

2 accepted papers

2026

Can Recommender Systems Teach Themselves? A Recursive Self-Improving Framework with Fidelity Control

ICML 2026poster

The scarcity of high-quality training data presents a fundamental bottleneck to scaling machine learning models. This challenge is particularly acute in recommendation systems, where extreme sparsity in user interactions leads to rugged optimization landscapes and poor generalization. We propose the…

Cited by 0SourceScholar
2025

From Feature Interaction to Feature Generation: A Generative Paradigm of CTR Prediction Models

ICML 2025poster

Click-Through Rate (CTR) prediction models estimate the probability of users clicking on items based on feature interactions, inherently following a discriminative paradigm. However, this paradigm is prone to embedding dimensional collapse and information redundancy due to limitations of vanilla fe…