18 citations · 34 across the 3 of their papers we have counts for
3 papers
cs.LG2021★ 2 cited
Federated Multiple Label Hashing (FedMLH): Communication Efficient Federated Learning on Extreme Classification Tasks
Zhenwei Dai, Chen Dun, Yuxin Tang +2
Federated learning enables many local devices to train a deep learning model jointly without sharing the local data. Currently, most of federated training schemes learns a global m…
cs.DS2019★ 14 cited
Adaptive Learned Bloom Filter (Ada-BF): Efficient Utilization of the Classifier
Zhenwei Dai, Anshumali Shrivastava
Recent work suggests improving the performance of Bloom filter by incorporating a machine learning model as a binary classifier. However, such learned Bloom filter does not take fu…
cs.LG2019★ 18 cited
Channel Normalization in Convolutional Neural Network avoids Vanishing Gradients
Zhenwei Dai, Reinhard Heckel
Normalization layers are widely used in deep neural networks to stabilize training. In this paper, we consider the training of convolutional neural networks with gradient descent o…