3 papers
cs.LG2026
LeAP: Learnable Adaptive Permutation for Feature Selection in Heterogeneous and Sparse Recommender Systems
Yihong Huang, Chen Chu, Fei Chen +3
Modern industrial recommender systems rely on thousands of heterogeneous features -- ranging from low-dimensional scalars (e.g., statistical value) to high-dimensional embeddings (…
cs.LG2025
DimGrow: Memory-Efficient Field-level Embedding Dimension Search
Yihong Huang, Chen Chu
Key feature fields need bigger embedding dimensionality, others need smaller. This demands automated dimension allocation. Existing approaches, such as pruning or Neural Architectu…
cs.LG2024
GradStop: Exploring Training Dynamics in Unsupervised Outlier Detection through Gradient
Yuang Zhang, Liping Wang, Yihong Huang +3
Unsupervised Outlier Detection (UOD) is a critical task in data mining and machine learning, aiming to identify instances that significantly deviate from the majority. Without any…