Zejiang Hou

According to our database, Zejiang Hou authored at least 23 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

SpeechGuard: Exploring the Adversarial Robustness of Multimodal Large Language Models.

Raghuveer Peri, Sai Muralidhar Jayanthi, Srikanth Ronanki, Anshu Bhatia, Karel Mundnich, Saket Dingliwal, Nilaksh Das, Zejiang Hou, Goeric Huybrechts, Srikanth Vishnubhotla, Daniel Garcia-Romero, Sundararajan Srinivasan, Kyu J. Han, Katrin Kirchhoff

CoRR, 2024

SpeechGuard: Exploring the Adversarial Robustness of Multi-modal Large Language Models.

Raghuveer Peri, Sai Muralidhar Jayanthi, Srikanth Ronanki, Anshu Bhatia, Karel Mundnich, Saket Dingliwal, Nilaksh Das, Zejiang Hou, Goeric Huybrechts, Srikanth Vishnubhotla, Daniel Garcia-Romero, Sundararajan Srinivasan, Kyu J. Han, Katrin Kirchhoff

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Semi-Supervised Few-Shot Learning Via Dependency Maximization and Instance Discriminant Analysis.

Zejiang Hou, Sun-Yuan Kung

J. Signal Process. Syst., January, 2023

2022

Meta-Learning the Difference: Preparing Large Language Models for Efficient Adaptation.

Zejiang Hou, Julian Salazar, George Polovets

Trans. Assoc. Comput. Linguistics, 2022

MILAN: Masked Image Pretraining on Language Assisted Representation.

Zejiang Hou, Fei Sun, Yen-Kuang Chen, Yuan Xie, Sun-Yuan Kung

CoRR, 2022

Multi-Dimensional Dynamic Model Compression for Efficient Image Super-Resolution.

Zejiang Hou, Sun-Yuan Kung

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Multi-Dimensional Model Compression of Vision Transformer.

Zejiang Hou, Sun-Yuan Kung

Proceedings of the IEEE International Conference on Multimedia and Expo, 2022

Effective Model Sparsification by Scheduled Grow-and-Prune Methods.

Xiaolong Ma, Minghai Qin, Fei Sun, Zejiang Hou, Kun Yuan, Yi Xu, Yanzhi Wang, Yen-Kuang Chen, Rong Jin, Yuan Xie

Proceedings of the Tenth International Conference on Learning Representations, 2022

CHEX: CHannel EXploration for CNN Model Compression.

Zejiang Hou, Minghai Qin, Fei Sun, Xiaolong Ma, Kun Yuan, Yi Xu, Yen-Kuang Chen, Rong Jin, Yuan Xie, Sun-Yuan Kung

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Multi-Dimensional Vision Transformer Compression via Dependency Guided Gaussian Process Search.

Zejiang Hou, Sun-Yuan Kung

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Semi-Supervised Few-Shot Learning from A Dependency-Discriminant Perspective.

Zejiang Hou, Sun-Yuan Kung

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.

Zejiang Hou, Sun-Yuan Kung

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.

Zejiang Hou, Anwar Walid, Sun-Yuan Kung

Proceedings of the IEEE International Conference on Acoustics, 2021

Parameter Efficient Dynamic Convolution via Tensor Decomposition.

Zejiang Hou, Sun-Yuan Kung

Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020

A Feature-map Discriminant Perspective for Pruning Deep Neural Networks.

Zejiang Hou, Sun-Yuan Kung

CoRR, 2020

Augment deep BP-parameter learning with local XAI-structural learning.

Sun-Yuan Kung, Zejiang Hou

Commun. Inf. Syst., 2020

A Discriminant Information Approach to Deep Neural Network Pruning.

Zejiang Hou, Sun-Yuan Kung

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Hierarchically Aggregated Residual Transformation for Single Image Super Resolution.

Zejiang Hou, Sun-Yuan Kung

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Efficient Image Super Resolution Via Channel Discriminative Deep Neural Network Pruning.

Zejiang Hou, Sun-Yuan Kung

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Scalable Kernel Learning Via the Discriminant Information.

Mert Al, Zejiang Hou, Sun-Yuan Kung

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

A Kernel Discriminant Information Approach to Non-linear Feature Selection.

Zejiang Hou, Sun-Yuan Kung

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.

Sun-Yuan Kung, Zejiang Hou, Yuchen Liu

Proceedings of the IEEE International Conference on Acoustics, 2019

2017

Distributed optimal power flow: An Augmented Lagrangian-Sequential Quadratic Programming approach.

Zejiang Hou, Ho-Chun Wu, Shing-Chow Chan

Proceedings of the IEEE International Symposium on Circuits and Systems, 2017