2024
Zero-resource Speech Translation and Recognition with LLMs.
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CoRR, 2024
SpeechGuard: Exploring the Adversarial Robustness of Multimodal Large Language Models.
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CoRR, 2024
Improving Multilingual ASR Robustness to Errors in Language Input.
Proceedings of the 25th Annual Conference of the International Speech Communication Association, 2024
Revisiting Convolution-free Transformer for Speech Recognition.
Proceedings of the 25th Annual Conference of the International Speech Communication Association, 2024
SpeechGuard: Exploring the Adversarial Robustness of Multi-modal Large Language Models.
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Proceedings of the Findings of the Association for Computational Linguistics, 2024
2023
Semi-Supervised Few-Shot Learning Via Dependency Maximization and Instance Discriminant Analysis.
J. Signal Process. Syst., January, 2023
2022
Meta-Learning the Difference: Preparing Large Language Models for Efficient Adaptation.
Trans. Assoc. Comput. Linguistics, 2022
MILAN: Masked Image Pretraining on Language Assisted Representation.
CoRR, 2022
Multi-Dimensional Dynamic Model Compression for Efficient Image Super-Resolution.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022
Multi-Dimensional Model Compression of Vision Transformer.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2022
Effective Model Sparsification by Scheduled Grow-and-Prune Methods.
Proceedings of the Tenth International Conference on Learning Representations, 2022
CHEX: CHannel EXploration for CNN Model Compression.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
Multi-Dimensional Vision Transformer Compression via Dependency Guided Gaussian Process Search.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022
Semi-Supervised Few-Shot Learning from A Dependency-Discriminant Perspective.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022
2021
Few-Shot Learning Via Dependency Maximization and Instance Discriminant Analysis.
Proceedings of the 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), 2021
Meta-Learning with Attention for Improved Few-Shot Learning.
Proceedings of the IEEE International Conference on Acoustics, 2021
Parameter Efficient Dynamic Convolution via Tensor Decomposition.
Proceedings of the 32nd British Machine Vision Conference 2021, 2021
2020
A Feature-map Discriminant Perspective for Pruning Deep Neural Networks.
CoRR, 2020
Augment deep BP-parameter learning with local XAI-structural learning.
Commun. Inf. Syst., 2020
A Discriminant Information Approach to Deep Neural Network Pruning.
Proceedings of the 25th International Conference on Pattern Recognition, 2020
Hierarchically Aggregated Residual Transformation for Single Image Super Resolution.
Proceedings of the 25th International Conference on Pattern Recognition, 2020
Efficient Image Super Resolution Via Channel Discriminative Deep Neural Network Pruning.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
Scalable Kernel Learning Via the Discriminant Information.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
2019
A Kernel Discriminant Information Approach to Non-linear Feature Selection.
Proceedings of the International Joint Conference on Neural Networks, 2019
Methodical Design and Trimming of Deep Learning Networks: Enhancing External BP Learning with Internal Omnipresent-supervision Training Paradigm.
Proceedings of the IEEE International Conference on Acoustics, 2019
2017
Distributed optimal power flow: An Augmented Lagrangian-Sequential Quadratic Programming approach.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2017