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Near-Optimal Sparse Allreduce for Distributed Deep Learning

Communication overhead is one of the major obstacles to train large deep...

Hardware-Efficient Deconvolution-Based GAN for Edge Computing

Generative Adversarial Networks (GAN) are cutting-edge algorithms for ge...

Scotch: An Efficient Secure Computation Framework for Secure Aggregation

Federated learning enables multiple data owners to jointly train a machi...

Direct Mutation and Crossover in Genetic Algorithms Applied to Reinforcement Learning Tasks

Neuroevolution has recently been shown to be quite competitive in reinfo...

A Survey on Training Challenges in Generative Adversarial Networks for Biomedical Image Analysis

In biomedical image analysis, the applicability of deep learning methods...

A Survey of Pretrained Language Models Based Text Generation

Text Generation aims to produce plausible and readable text in human lan...