refs.bib

@techreport{koopman97a,
author={Philip Koopman},
title={How to Write an Abstract},
institution={Carnegie Mellon University},
month={October},
year={1997},
note={\hfill\break
http://www.ece.cmu.edu/$\sim$koopman/essays/abstract.html},
}
@article{lecun1998gradient,
	title={Gradient-based learning applied to document recognition},
	author={LeCun, Yann and Bottou, L{\'e}on and Bengio, Yoshua and Haffner, Patrick and others},
	journal={Proceedings of the IEEE},
	volume={86},
	number={11},
	pages={2278--2324},
	year={1998},
	publisher={Taipei, Taiwan}
}
@article{xiao2017fashion,
	title={Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms},
	author={Xiao, Han and Rasul, Kashif and Vollgraf, Roland},
	journal={arXiv preprint arXiv:1708.07747},
	year={2017}
}
@misc{enum1,	
	author ={{Python Software Foundation}},	
	title = {{Enumerate}},	
	year =2019,
	note = "\url{https://docs.python.org/3/library/functions.html?highlight=enumerate#enumerate}",
	accessed = "Retrieved April 2019",	
}
@misc{pack,	
	author ={{GeeksForGeeks}},	
	title = {{Packing and Unpacking}},	
	year =2019,
	note = "\url{https://www.geeksforgeeks.org/packing-and-unpacking-arguments-in-python/}",
	accessed = "Retrieved April 2019",	
}
@article{pierce2010software,
	title={Software foundations},
	author={Pierce, Benjamin C and Casinghino, Chris and Gaboardi, Marco and Greenberg, Michael and Hri{\c{t}}cu, C{\u{a}}t{\u{a}}lin and Sjoberg, Vilhelm and Yorgey, Brent},
	journal={Webpage: http://www. cis. upenn. edu/bcpierce/sf/current/index. html},
	year={2010}
}

@inproceedings{pulina2010abstraction,
	title={An abstraction-refinement approach to verification of artificial neural networks},
	author={Pulina, Luca and Tacchella, Armando},
	booktitle={International Conference on Computer Aided Verification},
	pages={243--257},
	year={2010},
	organization={Springer}
}
@inproceedings{gehr2018ai2,
	title={Ai2: Safety and robustness certification of neural networks with abstract interpretation},
	author={Gehr, Timon and Mirman, Matthew and Drachsler-Cohen, Dana and Tsankov, Petar and Chaudhuri, Swarat and Vechev, Martin},
	booktitle={2018 IEEE Symposium on Security and Privacy (SP)},
	pages={3--18},
	year={2018},
	organization={IEEE}
}
@inproceedings{wang2018formal,
	title={Formal security analysis of neural networks using symbolic intervals},
	author={Wang, Shiqi and Pei, Kexin and Whitehouse, Justin and Yang, Junfeng and Jana, Suman},
	booktitle={27th $\{$USENIX$\}$ Security Symposium ($\{$USENIX$\}$ Security 18)},
	pages={1599--1614},
	year={2018}
}
@inproceedings{katz2017reluplex,
	title={Reluplex: An efficient SMT solver for verifying deep neural networks},
	author={Katz, Guy and Barrett, Clark and Dill, David L and Julian, Kyle and Kochenderfer, Mykel J},
	booktitle={International Conference on Computer Aided Verification},
	pages={97--117},
	year={2017},
	organization={Springer}
}
@article{jia2019taso,
	title={TASO: Optimizing Deep Learning Computation with Automatic Generation of Graph Substitutions},
	author={Jia, Zhihao and Padon, Oded and Thomas, James and Warszawski, Todd and Zaharia, Matei and Aiken, Alex},
	year={2019}
}
@article{du2018techniques,
	title={Techniques for interpretable machine learning},
	author={Du, Mengnan and Liu, Ninghao and Hu, Xia},
	journal={arXiv preprint arXiv:1808.00033},
	year={2018}
}
@inproceedings{abdul2018trends,
  title={Trends and trajectories for explainable, accountable and intelligible systems: An hci research agenda},
  author={Abdul, Ashraf and Vermeulen, Jo and Wang, Danding and Lim, Brian Y and Kankanhalli, Mohan},
  booktitle={Proceedings of the 2018 CHI conference on human factors in computing systems},
  pages={582},
  year={2018},
  organization={ACM}
}

@article{zhang2016understanding,
  title={Understanding deep learning requires rethinking generalization},
  author={Zhang, Chiyuan and Bengio, Samy and Hardt, Moritz and Recht, Benjamin and Vinyals, Oriol},
  journal={arXiv preprint arXiv:1611.03530},
  year={2016}
}

@inproceedings{adebayo2018sanity,
  title={Sanity checks for saliency maps},
  author={Adebayo, Julius and Gilmer, Justin and Muelly, Michael and Goodfellow, Ian and Hardt, Moritz and Kim, Been},
  booktitle={Advances in Neural Information Processing Systems},
  pages={9505--9515},
  year={2018}
}

@article{papernot2016towards,
  title={Towards the science of security and privacy in machine learning},
  author={Papernot, Nicolas and McDaniel, Patrick and Sinha, Arunesh and Wellman, Michael},
  journal={arXiv preprint arXiv:1611.03814},
  year={2016}
}

@inproceedings{goebel2018explainable,
  title={Explainable AI: the new 42?},
  author={Goebel, Randy and Chander, Ajay and Holzinger, Katharina and Lecue, Freddy and Akata, Zeynep and Stumpf, Simone and Kieseberg, Peter and Holzinger, Andreas},
  booktitle={International Cross-Domain Conference for Machine Learning and Knowledge Extraction},
  pages={295--303},
  year={2018},
  organization={Springer}
}

@inproceedings{anderson2019optimization,
  title={Optimization and abstraction: a synergistic approach for analyzing neural network robustness},
  author={Anderson, Greg and Pailoor, Shankara and Dillig, Isil and Chaudhuri, Swarat},
  booktitle={Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation},
  pages={731--744},
  year={2019},
  organization={ACM}
}

@article{lai2018human,
	title={On Human Predictions with Explanations and Predictions of Machine Learning Models: A Case Study on Deception Detection},
	author={Lai, Vivian and Tan, Chenhao},
	journal={arXiv preprint arXiv:1811.07901},
	year={2018}
}

@article{yang2019learn,
	title={Learn to Explain Efficiently via Neural Logic Inductive Learning},
	author={Yang, Yuan and Song, Le},
	journal={arXiv preprint arXiv:1910.02481},
	year={2019}
}

@inproceedings{ribeiro2016should,
	title={Why should i trust you?: Explaining the predictions of any classifier},
	author={Ribeiro, Marco Tulio and Singh, Sameer and Guestrin, Carlos},
	booktitle={Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining},
	pages={1135--1144},
	year={2016},
	organization={ACM}
}

@inproceedings{zhang2018interpretable,
	title={Interpretable convolutional neural networks},
	author={Zhang, Quanshi and Nian Wu, Ying and Zhu, Song-Chun},
	booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
	pages={8827--8836},
	year={2018}
}

@inproceedings{du2018towards,
	title={Towards explanation of dnn-based prediction with guided feature inversion},
	author={Du, Mengnan and Liu, Ninghao and Song, Qingquan and Hu, Xia},
	booktitle={Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery \& Data Mining},
	pages={1358--1367},
	year={2018},
	organization={ACM}
}
@inproceedings{sutskever2013importance,
	title={On the importance of initialization and momentum in deep learning},
	author={Sutskever, Ilya and Martens, James and Dahl, George and Hinton, Geoffrey},
	booktitle={International conference on machine learning},
	pages={1139--1147},
	year={2013}
}
@inproceedings{veale2018fairness,
	title={Fairness and accountability design needs for algorithmic support in high-stakes public sector decision-making},
	author={Veale, Michael and Van Kleek, Max and Binns, Reuben},
	booktitle={Proceedings of the 2018 chi conference on human factors in computing systems},
	pages={440},
	year={2018},
	organization={ACM}
}
@inproceedings{datta2016algorithmic,
	title={Algorithmic transparency via quantitative input influence: Theory and experiments with learning systems},
	author={Datta, Anupam and Sen, Shayak and Zick, Yair},
	booktitle={2016 IEEE symposium on security and privacy (SP)},
	pages={598--617},
	year={2016},
	organization={IEEE}
}
@inproceedings{pan2019static,
	title={Static deep neural network analysis for robustness},
	author={Pan, Rangeet},
	booktitle={Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering},
	pages={1238--1240},
	year={2019},
	organization={ACM}
}
@inproceedings{sampson2014expressing,
	title={Expressing and verifying probabilistic assertions},
	author={Sampson, Adrian and Panchekha, Pavel and Mytkowicz, Todd and McKinley, Kathryn S and Grossman, Dan and Ceze, Luis},
	booktitle={ACM SIGPLAN Notices},
	volume={49},
	number={6},
	pages={112--122},
	year={2014},
	organization={ACM}
}
@article{ingber2000adaptive,
	title={Adaptive simulated annealing (ASA): Lessons learned},
	author={Ingber, Lester},
	journal={arXiv preprint cs/0001018},
	year={2000}
}
@article{chollet2015keras,
	title={Keras documentation},
	author={Chollet, Fran{\c{c}}ois},
	journal={keras. io},
	year={2015}
}
@inproceedings{he2015delving,
  title={Delving deep into rectifiers: Surpassing human-level performance on imagenet classification},
  author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
  booktitle={Proceedings of the IEEE international conference on computer vision},
  pages={1026--1034},
  year={2015}
}
@inproceedings{jin2019auto,
	title={Auto-keras: An efficient neural architecture search system},
	author={Jin, Haifeng and Song, Qingquan and Hu, Xia},
	booktitle={Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery \& Data Mining},
	pages={1946--1956},
	year={2019},
	organization={ACM}
}
@inproceedings{zhao2017towards,
	title={Towards more accurate iris recognition using deeply learned spatially corresponding features},
	author={Zhao, Zijing and Kumar, Ajay},
	booktitle={Proceedings of the IEEE International Conference on Computer Vision},
	pages={3809--3818},
	year={2017}
}
@inproceedings{bergstra2011algorithms,
	title={Algorithms for hyper-parameter optimization},
	author={Bergstra, James S and Bardenet, R{\'e}mi and Bengio, Yoshua and K{\'e}gl, Bal{\'a}zs},
	booktitle={Advances in neural information processing systems},
	pages={2546--2554},
	year={2011}
}