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stat.ML2023
Quickest Change Detection for Unnormalized Statistical Models
Suya Wu, Enmao Diao, Taposh Banerjee +2
Classical quickest change detection algorithms require modeling pre-change and post-change distributions. Such an approach may not be feasible for various machine learning models b…
stat.ML2022★ 2 cited
A Theoretical Understanding of Neural Network Compression from Sparse Linear Approximation
Wenjing Yang, Ganghua Wang, Jie Ding +1
The goal of model compression is to reduce the size of a large neural network while retaining a comparable performance. As a result, computation and memory costs in resource-limite…