Efficient Detection and Filtering Systems for Distributed Training. (arXiv:2208.08085v3 [cs.LG] UPDATED)

A plethora of modern machine learning tasks requires the utilization of
large-scale distributed clusters as a critical component of the training
pipeline. However, abnormal Byzantine behavior of the worker nodes can derail
the training and compromise the quality of the inference. Such behavior can be
attributed to unintentional system malfunctions or orchestrated attacks; as a
result, some nodes may return arbitrary results to the parameter server (PS)
that coordinates the training. Recent work considers a wide range of attack
models …

detection distributed lg systems training