Kaidi Xu

According to our database1, Kaidi Xu authored at least 25 papers between 2017 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2020
Two-Timescale Hybrid Analog-Digital Beamforming for mmWave Full-Duplex MIMO Multiple-Relay Aided Systems.
IEEE J. Sel. Areas Commun., 2020

MIMO-Aided Nonlinear Hybrid Transceiver Design for Multiuser mmWave Systems Relying on Tomlinson-Harashima Precoding.
CoRR, 2020

Iterative Algorithm Induced Deep-Unfolding Neural Networks: Precoding Design for Multiuser MIMO Systems.
CoRR, 2020

Automatic Perturbation Analysis on General Computational Graphs.
CoRR, 2020

Defending against Backdoor Attack on Deep Neural Networks.
CoRR, 2020

Towards an Efficient and General Framework of Robust Training for Graph Neural Networks.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Light-weight Calibrator: A Separable Component for Unsupervised Domain Adaptation.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Evading Real-Time Person Detectors by Adversarial T-shirt.
CoRR, 2019

Min-Max Optimization without Gradients: Convergence and Applications to Adversarial ML.
CoRR, 2019

Brain-inspired reverse adversarial examples.
CoRR, 2019

Interpreting Adversarial Examples by Activation Promotion and Suppression.
CoRR, 2019

Second Rethinking of Network Pruning in the Adversarial Setting.
CoRR, 2019

Progressive DNN Compression: A Key to Achieve Ultra-High Weight Pruning and Quantization Rates using ADMM.
CoRR, 2019

ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Structured Adversarial Attack: Towards General Implementation and Better Interpretability.
Proceedings of the 7th International Conference on Learning Representations, 2019

On the Design of Black-Box Adversarial Examples by Leveraging Gradient-Free Optimization and Operator Splitting Method.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Adversarial Robustness vs. Model Compression, or Both?
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

REQ-YOLO: A Resource-Aware, Efficient Quantization Framework for Object Detection on FPGAs.
Proceedings of the 2019 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2019

ADMM attack: an enhanced adversarial attack for deep neural networks with undetectable distortions.
Proceedings of the 24th Asia and South Pacific Design Automation Conference, 2019

2018
Progressive Weight Pruning of Deep Neural Networks using ADMM.
CoRR, 2018

Structured Adversarial Attack: Towards General Implementation and Better Interpretability.
CoRR, 2018

Reinforced Adversarial Attacks on Deep Neural Networks Using ADMM.
Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018

2017
Supervised graph hashing for histopathology image retrieval and classification.
Medical Image Anal., 2017

Asymmetric Discrete Graph Hashing.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017


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