1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.LG2020★ 1 cited
Bounding The Number of Linear Regions in Local Area for Neural Networks with ReLU Activations
Rui Zhu, Bo Lin, Haixu Tang
The number of linear regions is one of the distinct properties of the neural networks using piecewise linear activation functions such as ReLU, comparing with those conventional on…
cs.CV2020
Towards Fair Cross-Domain Adaptation via Generative Learning
Tongxin Wang, Zhengming Ding, Wei Shao +2
Domain Adaptation (DA) targets at adapting a model trained over the well-labeled source domain to the unlabeled target domain lying in different distributions. Existing DA normally…