Zhao Kang

Exploiting Nonlinear Relationships for Top-N Recommender Systems

2017

To alleviate the information overload problem, recommendation technology has emerged and flourished. %As a most widely used recommendation technique, collaborative filtering algorithms suffer from data sparseness and cold start problems. Consequently, it is difficult to …

Large-scale Multi-view Subspace Clustering in Linear Time

2019 · arXiv (Cornell University)

A plethora of multi-view subspace clustering (MVSC) methods have been proposed over the past few years. Researchers manage to boost clustering accuracy from different points of view. However, many state-of-the-art MVSC algorithms, typically have a …

Structure-Preserving Graph Representation Learning

2022 · 2022 IEEE International Conference on Data Mining (ICDM)

Though graph representation learning (GRL) has made significant progress, it is still a challenge to extract and embed the rich topological structure and feature information in an adequate way. Most existing methods focus on local …

On the Benefits of Attribute-Driven Graph Domain Adaptation

2025 · arXiv (Cornell University)

Graph Domain Adaptation (GDA) addresses a pressing challenge in cross-network learning, particularly pertinent due to the absence of labeled data in real-world graph datasets. Recent studies attempted to learn domain invariant representations by eliminating structural …