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10/12/2022
An Ensemble Teacher-Student Learning Approach with Poisson Sub-sampling to Differential Privacy Preserving Speech Recognition
We propose an ensemble learning framework with Poisson sub-sampling to e...
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08/15/2022
Federated Quantum Natural Gradient Descent for Quantum Federated Learning
The heart of Quantum Federated Learning (QFL) is associated with a distr...
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06/08/2022
Theoretical Error Performance Analysis for Variational Quantum Circuit Based Functional Regression
The noisy intermediate-scale quantum (NISQ) devices enable the implement...
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03/11/2022
Exploiting Low-Rank Tensor-Train Deep Neural Networks Based on Riemannian Gradient Descent With Illustrations of Speech Processing
This work focuses on designing low complexity hybrid tensor networks by ...
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02/17/2022
When BERT Meets Quantum Temporal Convolution Learning for Text Classification in Heterogeneous Computing
The rapid development of quantum computing has demonstrated many unique ...
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01/11/2022
Exploiting Hybrid Models of Tensor-Train Networks for Spoken Command Recognition
This work aims to design a low complexity spoken command recognition (SC...
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10/17/2021
Classical-to-Quantum Transfer Learning for Spoken Command Recognition Based on Quantum Neural Networks
This work investigates an extension of transfer learning applied in mach...
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10/06/2021
QTN-VQC: An End-to-End Learning framework for Quantum Neural Networks
The advent of noisy intermediate-scale quantum (NISQ) computers raises a...
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10/26/2020
Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech Recognition
We propose a novel decentralized feature extraction approach in federate...
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09/06/2020
MFL_COVID19: Quantifying Country-based Factors affecting Case Fatality Rate in Early Phase of COVID-19 Epidemic via Regularised Multi-task Feature Learning
Recent outbreak of COVID-19 has led a rapid global spread around the wor...
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08/23/2020
Variational Inference-Based Dropout in Recurrent Neural Networks for Slot Filling in Spoken Language Understanding
This paper proposes to generalize the variational recurrent neural netwo...
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08/12/2020
On Mean Absolute Error for Deep Neural Network Based Vector-to-Vector Regression
In this paper, we exploit the properties of mean absolute error (MAE) as...
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08/04/2020
Analyzing Upper Bounds on Mean Absolute Errors for Deep Neural Network Based Vector-to-Vector Regression
In this paper, we show that, in vector-to-vector regression utilizing de...
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07/25/2020
Exploring Deep Hybrid Tensor-to-Vector Network Architectures for Regression Based Speech Enhancement
This paper investigates different trade-offs between the number of model...
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03/31/2020
Characterizing Speech Adversarial Examples Using Self-Attention U-Net Enhancement
Recent studies have highlighted adversarial examples as ubiquitous threa...
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02/20/2020
Enhanced Adversarial Strategically-Timed Attacks against Deep Reinforcement Learning
Recent deep neural networks based techniques, especially those equipped ...
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02/03/2020
Tensor-to-Vector Regression for Multi-channel Speech Enhancement based on Tensor-Train Network
We propose a tensor-to-vector regression approach to multi-channel speec...
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01/27/2020
Submodular Rank Aggregation on Score-based Permutations for Distributed Automatic Speech Recognition
Distributed automatic speech recognition (ASR) requires to aggregate out...
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07/04/2017