5 citations · 9 across the 3 of their papers we have counts for
4 papers
Exact Count of Boundary Pieces of ReLU Classifiers: Towards the Proper Complexity Measure for Classification
Paweł Piwek, Adam Klukowski, Tianyang Hu
Classic learning theory suggests that proper regularization is the key to good generalization and robustness. In classification, current training schemes only target the complexity…
ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization
Qishi Dong, Awais Muhammad, Fengwei Zhou +5
Recent advances on large-scale pre-training have shown great potentials of leveraging a large set of Pre-Trained Models (PTMs) for improving Out-of-Distribution (OoD) generalizatio…
Sharp Rate of Convergence for Deep Neural Network Classifiers under the Teacher-Student Setting
Tianyang Hu, Zuofeng Shang, Guang Cheng
Classifiers built with neural networks handle large-scale high dimensional data, such as facial images from computer vision, extremely well while traditional statistical methods of…
Stein Neural Sampler
Tianyang Hu, Zixiang Chen, Hanxi Sun +3
We propose two novel samplers to generate high-quality samples from a given (un-normalized) probability density. Motivated by the success of generative adversarial networks, we con…