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Sijia Liu

Preserving Earlier Knowledge in Continual Learning with the Help of All Previous Feature Extractors


Apr 28, 2021
Zhuoyun Li, Changhong Zhong, Sijia Liu, Ruixuan Wang, Wei-Shi Zheng

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Preserve, Promote, or Attack? GNN Explanation via Topology Perturbation


Mar 25, 2021
Yi Sun, Abel Valente, Sijia Liu, Dakuo Wang

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Generating Adversarial Computer Programs using Optimized Obfuscations


Mar 18, 2021
Shashank Srikant, Sijia Liu, Tamara Mitrovska, Shiyu Chang, Quanfu Fan, Gaoyuan Zhang, Una-May O'Reilly

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* This work will be published at ICLR 2021 
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On Instabilities of Conventional Multi-Coil MRI Reconstruction to Small Adverserial Perturbations


Feb 25, 2021
Chi Zhang, Jinghan Jia, Burhaneddin Yaman, Steen Moeller, Sijia Liu, Mingyi Hong, Mehmet Akçakaya

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* To appear in Proceedings of the 29th Annual Meeting of ISMRM, 2021 
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On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning


Feb 20, 2021
Ren Wang, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Chuang Gan, Meng Wang

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Lottery Ticket Implies Accuracy Degradation, Is It a Desirable Phenomenon?


Feb 19, 2021
Ning Liu, Geng Yuan, Zhengping Che, Xuan Shen, Xiaolong Ma, Qing Jin, Jian Ren, Jian Tang, Sijia Liu, Yanzhi Wang

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Fast Training of Provably Robust Neural Networks by SingleProp


Feb 01, 2021
Akhilan Boopathy, Tsui-Wei Weng, Sijia Liu, Pin-Yu Chen, Gaoyuan Zhang, Luca Daniel

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* Published at AAAI 2021 
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Achieving Real-Time LiDAR 3D Object Detection on a Mobile Device


Dec 26, 2020
Pu Zhao, Wei Niu, Geng Yuan, Yuxuan Cai, Hsin-Hsuan Sung, Wujie Wen, Sijia Liu, Xipeng Shen, Bin Ren, Yanzhi Wang, Xue Lin

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Self-Progressing Robust Training


Dec 22, 2020
Minhao Cheng, Pin-Yu Chen, Sijia Liu, Shiyu Chang, Cho-Jui Hsieh, Payel Das

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* Accepted in AAAI2021 
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Zeroth-Order Hybrid Gradient Descent: Towards A Principled Black-Box Optimization Framework


Dec 21, 2020
Pranay Sharma, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Xue Lin, Pramod K. Varshney

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* 27 pages, 3 figures 
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The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models


Dec 12, 2020
Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Michael Carbin, Zhangyang Wang

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6.7ms on Mobile with over 78% ImageNet Accuracy: Unified Network Pruning and Architecture Search for Beyond Real-Time Mobile Acceleration


Dec 01, 2020
Zhengang Li, Geng Yuan, Wei Niu, Yanyu Li, Pu Zhao, Yuxuan Cai, Xuan Shen, Zheng Zhan, Zhenglun Kong, Qing Jin, Zhiyu Chen, Sijia Liu, Kaiyuan Yang, Bin Ren, Yanzhi Wang, Xue Lin

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Learned Fine-Tuner for Incongruous Few-Shot Learning


Oct 20, 2020
Pu Zhao, Sijia Liu, Parikshit Ram, Songtao Lu, Djallel Bouneffouf, Xue Lin

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Training Stronger Baselines for Learning to Optimize


Oct 18, 2020
Tianlong Chen, Weiyi Zhang, Jingyang Zhou, Shiyu Chang, Sijia Liu, Lisa Amini, Zhangyang Wang

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* NeurIPS 2020 Spotlight Oral 
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Higher-Order Certification for Randomized Smoothing


Oct 13, 2020
Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel

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* Accepted to NeurIPS2020(spotlight) 
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TimeAutoML: Autonomous Representation Learning for Multivariate Irregularly Sampled Time Series


Oct 04, 2020
Yang Jiao, Kai Yang, Shaoyu Dou, Pan Luo, Sijia Liu, Dongjin Song

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Achieving Real-Time Execution of Transformer-based Large-scale Models on Mobile with Compiler-aware Neural Architecture Optimization


Sep 15, 2020
Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang

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Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases


Jul 31, 2020
Ren Wang, Gaoyuan Zhang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong, Meng Wang

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The Lottery Ticket Hypothesis for Pre-trained BERT Networks


Jul 23, 2020
Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Zhangyang Wang, Michael Carbin


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Solving Constrained CASH Problems with ADMM


Jul 11, 2020
Parikshit Ram, Sijia Liu, Deepak Vijaykeerthi, Dakuo Wang, Djallel Bouneffouf, Greg Bramble, Horst Samulowitz, Alexander G. Gray

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* 7th ICML Workshop on Automated Machine Learning (2020) 
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Proper Network Interpretability Helps Adversarial Robustness in Classification


Jun 26, 2020
Akhilan Boopathy, Sijia Liu, Gaoyuan Zhang, Cynthia Liu, Pin-Yu Chen, Shiyu Chang, Luca Daniel

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* 22 pages, 9 figures, Published at ICML 2020 
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Can 3D Adversarial Logos Cloak Humans?


Jun 25, 2020
Tianlong Chen, Yi Wang, Jingyang Zhou, Sijia Liu, Shiyu Chang, Chandrajit Bajaj, Zhangyang Wang

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Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case


Jun 25, 2020
Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong

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* International Conference on Machine Learning (ICML 2020) 
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A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning


Jun 21, 2020
Sijia Liu, Pin-Yu Chen, Bhavya Kailkhura, Gaoyuan Zhang, Alfred Hero, Pramod K. Varshney

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* IEEE Signal Processing Magazine 
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Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning


Mar 28, 2020
Tianlong Chen, Sijia Liu, Shiyu Chang, Yu Cheng, Lisa Amini, Zhangyang Wang

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* CVPR 2020 
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Rethinking Randomized Smoothing for Adversarial Robustness


Mar 02, 2020
Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei, Weng, Sijia Liu, Pin-Yu Chen, Luca Daniel

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* Jeet Mohapatra and Ching-Yun Ko contributed equally 
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Defending against Backdoor Attack on Deep Neural Networks


Feb 26, 2020
Hao Cheng, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Pu Zhao, Xue Lin

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* Accepted by KDD 2019 AdvML workshop 
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