13 citations · 43 across the 18 of their papers we have counts for
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cs.LG2023★ 13 cited
Learning to Grow Pretrained Models for Efficient Transformer Training
Peihao Wang, Rameswar Panda, Lucas Torroba Hennigen +6
Scaling transformers has led to significant breakthroughs in many domains, leading to a paradigm in which larger versions of existing models are trained and released on a periodic…
cs.LG2023★ 1 cited
Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach
Han Guo, Philip Greengard, Hongyi Wang +3
The canonical formulation of federated learning treats it as a distributed optimization problem where the model parameters are optimized against a global loss function that decompo…