3 papers
cs.LG2025
DeepCQ: General-Purpose Deep-Surrogate Framework for Lossy Compression Quality Prediction
Khondoker Mirazul Mumenin, Robert Underwood, Dong Dai +4
Error-bounded lossy compression techniques have become vital for scientific data management and analytics, given the ever-increasing volume of data generated by modern scientific s…
cs.LG2025
Rethinking the Potential of Layer Freezing for Efficient DNN Training
Chence Yang, Ci Zhang, Lei Lu +11
With the growing size of deep neural networks and datasets, the computational costs of training have significantly increased. The layer-freezing technique has recently attracted gr…
cs.DC2025
NeurLZ: An Online Neural Learning-Based Method to Enhance Scientific Lossy Compression
Wenqi Jia, Zhewen Hu, Youyuan Liu +10
Large-scale scientific simulations generate massive datasets, posing challenges for storage and I/O. Traditional lossy compression struggles to advance more in balancing compressio…