12 citations · 16 across the 5 of their papers we have counts for
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cs.LG2022
Exploiting Low-Rank Tensor-Train Deep Neural Networks Based on Riemannian Gradient Descent With Illustrations of Speech Processing
Jun Qi, Chao-Han Huck Yang, Pin-Yu Chen +1
This work focuses on designing low complexity hybrid tensor networks by considering trade-offs between the model complexity and practical performance. Firstly, we exploit a low-ran…
cs.LG2021★ 12 cited
Classical-to-Quantum Transfer Learning for Spoken Command Recognition Based on Quantum Neural Networks
Jun Qi, Javier Tejedor
This work investigates an extension of transfer learning applied in machine learning algorithms to the emerging hybrid end-to-end quantum neural network (QNN) for spoken command re…
cs.LG2017★ 3 cited
Unsupervised Submodular Rank Aggregation on Score-based Permutations
Jun Qi, Xu Liu, Javier Tejedor +1
Unsupervised rank aggregation on score-based permutations, which is widely used in many applications, has not been deeply explored yet. This work studies the use of submodular opti…