Zhijie Chen

Towards Interpretable Feature Representation for Domain Adaptation Problem

2022

Deep convolutional neural networks (CNNs) have witnessed a great progress in visual recognition over the past years. However, deep CNN models are still suffering from the domain adaptation problem. Most of the existing methods try …

Sketched Adaptive Federated Deep Learning: A Sharp Convergence Analysis

2024 · arXiv (Cornell University)

Combining gradient compression methods (e.g., CountSketch, quantization) and adaptive optimizers (e.g., Adam, AMSGrad) is a desirable goal in federated learning (FL), with potential benefits on both fewer communication rounds and less per-round communication. In spite …