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Intensive algorithmic efforts have been made to enable the rapid improvements of certificated robustness for complex ML models recently.
The complexity of computing the permanent
L.G. Valiant · 1979
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Causality: Models, Reasoning, and Inference
Judea Pearl · 2000
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Markov logic networks
Matthew Richardson and Pedro Domingos · 2006
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Markov logic networks
Matthew Richardson and Pedro Domingos · 2006
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Efficient weight learning for markov logic networks
Daniel Lowd and Pedro Domingos · 2007
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Joint inference in information extraction
Hoifung Poon and Pedro Domingos · 2007
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Graphical models, exponential families, and variational inference
Martin J. Wainwright and Michael I. Jordan · 2008
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ImageNet: A Large-Scale Hierarchical Image Database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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Max-margin weight learning for markov logic networks
Tuyen N Huynh and Raymond J Mooney · 2009
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Joint inference for natural language processing
Andrew McCallum · 2009
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Protein fold recognition using markov logic networks
Marenglen Biba, Stefano Ferilli, and Floriana Esposito · 2011
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Bayesian networks
Judea Pearl · 2011
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Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition
Johannes Stallkamp, Marc Schlipsing, Jan Salmen, and Christian Igel · 2012
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Joint inference of multiple label types in large networks
Deepayan Chakrabarti, Stanislav Funiak, Jonathan Chang, and Sofus A Macskassy · 2014
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Joint inference for knowledge base population
Liwei Chen, Yansong Feng, Jinghui Mo, Songfang Huang, and Dongyan Zhao · 2014
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Large-scale object classification using label relation graphs
Jia Deng, Nan Ding, Yangqing Jia, Andrea Frome, Kevin Murphy, Samy Bengio, Yuan Li, Hartmut Neven, and Hartwig Adam · 2014
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Using structured events to predict stock price movement: An empirical investigation
Xiao Ding, Yue Zhang, Ting Liu, and Junwen Duan · 2014
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Feature cross-substitution in adversarial classification
Bo Li and Yevgeniy Vorobeychik · 2014
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A machine reading system for assembling synthetic paleontological databases
Shanan E. Peters, Ce Zhang, Miron Livny, and Christopher Ré · 2014
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Learning deep structured models
Liang-Chieh Chen, Alexander Schwing, Alan Yuille, and Raquel Urtasun · 2015
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Explaining and harnessing adversarial examples
Ian J. Goodfellow, Jonathon Shlens, and Christian Szegedy · 2015
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Large-scale extraction of gene interactions from full-text literature using DeepDive
Emily K. Mallory, Ce Zhang, Christopher Ré, and Russ B. Altman · 2015
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Towards evaluating the robustness of neural networks
Nicholas Carlini and David Wagner · 2017
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Provable defenses against adversarial examples via the convex outer adversarial polytope
J Zico Kolter and Eric Wong · 2017
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Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2017
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Evaluating robustness of neural networks with mixed integer programming
Vincent Tjeng, Kai Xiao, and Russ Tedrake · 2017
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Deepdive: Declarative knowledge base construction
Ce Zhang, Christopher Ré, Michael Cafarella, Christopher De Sa, Alex Ratner, Jaeho Shin, Feiran Wang, and Sen Wu · 2017
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Advit: Adversarial frames identifier based on temporal consistency in videos
Chaowei Xiao, Ruizhi Deng, Bo Li, Taesung Lee, Benjamin Edwards, Jinfeng Yi, Dawn Song, Mingyan Liu, and Ian Molloy · 2019
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Joint inference of reward machines and policies for reinforcement learning
Zhe Xu, Ivan Gavran, Yousef Ahmad, Rupak Majumdar, Daniel Neider, Ufuk Topcu, and Bo Wu · 2019
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Consistency regularization for certified robustness of smoothed classifiers
Jongheon Jeong and Jinwoo Shin · 2020
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Complex markov logic networks: Expressivity and liftability
Ondrej Kuzelka · 2020
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Qeba: Query-efficient boundary-based blackbox attack
Huichen Li, Xiaojun Xu, Xiaolu Zhang, Shuang Yang, and Bo Li · 2020
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Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples
Anish Athalye, Nicholas Carlini, and David Wagner · 2018
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Robust physical-world attacks on deep learning visual classification
Kevin Eykholt, Ivan Evtimov, Earlence Fernandes, Bo Li, Amir Rahmati, Chaowei Xiao, Atul Prakash, Tadayoshi Kohno, and Dawn Song · 2018
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On the effectiveness of interval bound propagation for training verifiably robust models
Sven Gowal, Krishnamurthy Dvijotham, Robert Stanforth, Rudy Bunel, Chongli Qin, Jonathan Uesato, Relja Arandjelovic, Timothy Mann, and Pushmeet Kohli · 2018
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Characterizing adversarial subspaces using local intrinsic dimensionality
Xingjun Ma, Bo Li, Yisen Wang, Sarah M Erfani, Sudanthi Wijewickrema, Grant Schoenebeck, Dawn Song, Michael E Houle, and James Bailey · 2018
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Ensemble adversarial training: Attacks and defenses
Florian Tramèr, Alexey Kurakin, Nicolas Papernot, Dan Boneh, and Patrick McDaniel · 2018
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Robustness may be at odds with accuracy)
Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, and Aleksander Madry · 2018
Cited alongside, same era.
Towards fast computation of certified robustness for relu networks
Lily Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Luca Daniel, Duane Boning, and Inderjit Dhillon · 2018
Cited alongside, same era.
Linyi Li, Xiangyu Qi, Tao Xie, and Bo Li · 2020
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Semanticadv: Generating adversarial examples via attribute-conditioned image editing
Haonan Qiu, Chaowei Xiao, Lei Yang, Xinchen Yan, Honglak Lee, and Bo Li · 2020
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On adaptive attacks to adversarial example defenses
Florian Tramer, Nicholas Carlini, Wieland Brendel, and Aleksander Madry · 2020
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Automatic perturbation analysis for scalable certified robustness and beyond
Kaidi Xu, Zhouxing Shi, Huan Zhang, Yihan Wang, Kai-Wei Chang, Minlie Huang, Bhavya Kailkhura, Xue Lin, and Cho-Jui Hsieh · 2020
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Randomized smoothing of all shapes and sizes
Greg Yang, Tony Duan, J Edward Hu, Hadi Salman, Ilya Razenshteyn, and Jerry Li · 2020
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Knowledge enhanced machine learning pipeline against diverse adversarial attacks
Nezihe Merve Gürel, Xiangyu Qi, Luka Rimanic, Ce Zhang, and Bo Li · 2021
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Nonlinear gradient estimation for query efficient blackbox attack
Huichen Li, Linyi Li, Xiaojun Xu, Xiaolu Zhang, Shuang Yang, and Bo Li · 2021
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Tss: Transformation-specific smoothing for robustness certification
Linyi Li, Maurice Weber, Xiaojun Xu, Luka Rimanic, Bhavya Kailkhura, Tao Xie, Ce Zhang, and Bo Li · 2021
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Editing a classifier by rewriting its prediction rules
Shibani Santurkar, Dimitris Tsipras, Mahalaxmi Elango, David Bau, Antonio Torralba, and Aleksander Madry · 2021
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On the certified robustness for ensemble models and beyond
Zhuolin Yang, Linyi Li, Xiaojun Xu, Bhavya Kailkhura, Tao Xie, and Bo Li · 2021
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Trs: Transferability reduced ensemble via promoting gradient diversity and model smoothness
Zhuolin Yang, Linyi Li, Xiaojun Xu, Shiliang Zuo, Qian Chen, Pan Zhou, Benjamin I. P. Rubinstein, Ce Zhang, and Bo Li · 2021
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Trs: Transferability reduced ensemble via promoting gradient diversity and model smoothness
Zhuolin Yang, Linyi Li, Xiaojun Xu, Shiliang Zuo, Qian Chen, Pan Zhou, Benjamin I P Rubinstein, Ce Zhang, and Bo Li · 2021
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Double sampling randomized smoothing
Linyi Li, Jiawei Zhang, Tao Xie, and Bo Li · 2022
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On the certified robustness for ensemble models and beyond
Zhuolin Yang, Linyi Li, Xiaojun Xu, Bhavya Kailkhura, Tao Xie, and Bo Li · 2022
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Improving certified robustness via statistical learning with logical reasoning
Zhuolin Yang, Zhikuan Zhao, Boxin Wang, Jiawei Zhang, Linyi Li, Hengzhi Pei, Bojan Karlaš, Ji Liu, Heng Guo, Ce Zhang, and Bo Li · 2022
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Progressive-scale boundary blackbox attack via projective gradient estimation
Jiawei Zhang, Linyi Li, Huichen Li, Xiaolu Zhang, Shuang Yang, and Bo Li · 2022
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