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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Towards an Efficient and General Framework of Robust Training for Graph Neural Networks

Feb 25, 2020
Kaidi Xu, Sijia Liu, Pin-Yu Chen, Mengshu Sun, Caiwen Ding, Bhavya Kailkhura, Xue Lin

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* Accepted by ICASSP 2020 

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An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices

Feb 22, 2020
Xiaolong Ma, Wei Niu, Tianyun Zhang, Sijia Liu, Sheng Lin, Hongjia Li, Xiang Chen, Jian Tang, Kaisheng Ma, Bin Ren, Yanzhi Wang

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* arXiv admin note: text overlap with arXiv:1909.05073 

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SS-Auto: A Single-Shot, Automatic Structured Weight Pruning Framework of DNNs with Ultra-High Efficiency

Jan 23, 2020
Zhengang Li, Yifan Gong, Xiaolong Ma, Sijia Liu, Mengshu Sun, Zheng Zhan, Zhenglun Kong, Geng Yuan, Yanzhi Wang

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Towards Verifying Robustness of Neural Networks Against Semantic Perturbations

Dec 19, 2019
Jeet Mohapatra, Tsui-Wei, Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel

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Adversarial T-shirt! Evading Person Detectors in A Physical World

Nov 27, 2019
Kaidi Xu, Gaoyuan Zhang, Sijia Liu, Quanfu Fan, Mengshu Sun, Hongge Chen, Pin-Yu Chen, Yanzhi Wang, Xue Lin

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Development of Clinical Concept Extraction Applications: A Methodology Review

Oct 28, 2019
Sunyang Fu, David Chen, Sijia Liu, Sungrim Moon, Kevin J Peterson, Feichen Shen, Yanshan Wang, Liwei Wang, Andrew Wen, Yiqing Zhao, Sunghwan Sohn, Hongfang Liu

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How can AI Automate End-to-End Data Science?

Oct 22, 2019
Charu Aggarwal, Djallel Bouneffouf, Horst Samulowitz, Beat Buesser, Thanh Hoang, Udayan Khurana, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander Gray

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Evading Real-Time Person Detectors by Adversarial T-shirt

Oct 18, 2019
Kaidi Xu, Gaoyuan Zhang, Sijia Liu, Quanfu Fan, Mengshu Sun, Hongge Chen, Pin-Yu Chen, Yanzhi Wang, Xue Lin

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An Information-Theoretic Perspective on the Relationship Between Fairness and Accuracy

Oct 17, 2019
Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, Kush R. Varshney

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ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization

Oct 16, 2019
Xiangyi Chen, Sijia Liu, Kaidi Xu, Xingguo Li, Xue Lin, Mingyi Hong, David Cox

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Min-Max Optimization without Gradients: Convergence and Applications to Adversarial ML

Sep 30, 2019
Sijia Liu, Songtao Lu, Xiangyi Chen, Yao Feng, Kaidi Xu, Abdullah Al-Dujaili, Minyi Hong, Una-May Obelilly

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