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Found 4 papers, 1 papers with code
Accelerating Large Batch Training via Gradient Signal to Noise Ratio (GSNR)
As models for nature language processing (NLP), computer vision (CV) and recommendation systems (RS) require surging computation, a large number of GPUs/TPUs are paralleled as a large batch (LB) to improve training throughput.
Transforming the Latent Space of StyleGAN for Real Face Editing
But more importantly, the proposed $W$++ space achieves superior performance in both reconstruction quality and editing quality.
Investigating Label Bias in Beam Search for Open-ended Text Generation
However, in open-ended text generation, beam search is often found to produce repetitive and generic texts, sampling-based decoding algorithms like top-k sampling and nucleus sampling are more preferred.
Understanding Why Neural Networks Generalize Well Through GSNR of Parameters
As deep neural networks (DNNs) achieve tremendous success across many application domains, researchers tried to explore in many aspects on why they generalize well.
