Brian Van Essen

meProp: sparsified back propagation for accelerated deep learning with reduced overfitting

Review of deep learning: concepts, CNN architectures, challenges, applications, future directions

Model Compression and Hardware Acceleration for Neural Networks: A Comprehensive Survey

Model Pruning Enables Efficient Federated Learning on Edge Devices

Embedded System Design

What is Semantic Communication? A View on Conveying Meaning in the Era of Machine Intelligence

A Survey of Methods for Analyzing and Improving GPU Energy Efficiency

Adaptive Federated Learning in Resource Constrained Edge Computing Systems

Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning

Communication quantization for data-parallel training of deep neural networks

Accelerating a Random Forest Classifier: Multi-Core, GP-GPU, or FPGA?

Communication Quantization for Data-Parallel Training of Deep Neural Networks

LBANN