Showing 2023 · stat.MLShow all
2 papers · 2 filters
stat.ML2023
Understanding the Generalization Ability of Deep Learning Algorithms: A Kernelized Renyi's Entropy Perspective
Yuxin Dong, Tieliang Gong, Hong Chen +1
Recently, information theoretic analysis has become a popular framework for understanding the generalization behavior of deep neural networks. It allows a direct analysis for stoch…
stat.ML2023
On the Stability and Generalization of Triplet Learning
Jun Chen, Hong Chen, Xue Jiang +4
Triplet learning, i.e. learning from triplet data, has attracted much attention in computer vision tasks with an extremely large number of categories, e.g., face recognition and pe…