Lizhong Ding

On the Decision Boundary of Deep Neural Networks

2018 · arXiv (Cornell University)

While deep learning models and techniques have achieved great empirical success, our understanding of the source of success in many aspects remains very limited. In an attempt to bridge the gap, we investigate the decision …

Learning Vector-valued Functions with Local Rademacher Complexity and Unlabeled Data

2019 · arXiv (Cornell University)

We consider a general family of problems of which the output space admits vector-valued structure, covering a broad family of important domains, e.g. multi-label learning and multi-class classification. By using local Rademacher complexity and unlabeled …