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cs.LG2023
Exploiting Symmetric Temporally Sparse BPTT for Efficient RNN Training
Xi Chen, Chang Gao, Zuowen Wang +4
Recurrent Neural Networks (RNNs) are useful in temporal sequence tasks. However, training RNNs involves dense matrix multiplications which require hardware that can support a large…
cs.LG2019★ 8 cited
Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness
Fanny Yang, Zuowen Wang, Christina Heinze-Deml
This work provides theoretical and empirical evidence that invariance-inducing regularizers can increase predictive accuracy for worst-case spatial transformations (spatial robustn…