related work + conclusion

1 files changed, 77 insertions, 1 deletions

diff --git a/references.bib b/references.bib
index 303b83f..e3a73fc 100644
--- a/references.bib
+++ b/references.bib
@@ -150,4 +150,80 @@
 	journal={Department of Computer Science, The University of Iowa, Tech. Rep},
 	year={2016}
 }
-
+@misc{wang2018efficientformalsafetyanalysis,
+      title={Efficient Formal Safety Analysis of Neural Networks}, 
+      author={Shiqi Wang and Kexin Pei and Justin Whitehouse and Junfeng Yang and Suman Jana},
+      year={2018},
+      eprint={1809.08098},
+      archivePrefix={arXiv},
+      primaryClass={cs.LG},
+      url={https://arxiv.org/abs/1809.08098}, 
+}
+@incollection{dantzig1947simplex,
+  abstract = {In 1947, George Dantzig created a simplex algorithm to solve linear programs for planning and decision-making in large-scale enterprises. The algorithm's success led to a vast array of specializations and generalizations that have dominated practical operations research for half a century},
+  added-at = {2010-02-26T23:23:28.000+0100},
+  address = {Piscataway, NJ, USA},
+  author = {Nash, John C.},
+  biburl = {https://www.bibsonomy.org/bibtex/2b85e2108e8f7cc402a52577323035ad9/ytyoun},
+  booktitle = {Computing in Science and Engg.},
+  doi = {10.1109/5992.814654},
+  interhash = {5fb3b9e4a0e81f7811c917b86d1097cb},
+  intrahash = {b85e2108e8f7cc402a52577323035ad9},
+  issn = {1521-9615},
+  keywords = {algorithm magazine matrix simplex top.ten.algorithms},
+  number = 1,
+  pages = {29--31},
+  publisher = {IEEE Educational Activities Department},
+  timestamp = {2015-12-13T09:44:24.000+0100},
+  title = {The (Dantzig) Simplex Method for Linear Programming},
+  volume = 2,
+  year = 2000
+}
+@article{zhang2018efficient,
+  title={Efficient Neural Network Robustness Certification with General Activation Functions},
+  author={Zhang, Huan and Weng, Tsui-Wei and Chen, Pin-Yu and Hsieh, Cho-Jui and Daniel, Luca},
+  journal={Advances in Neural Information Processing Systems},
+  volume={31},
+  pages={4939--4948},
+  year={2018},
+  url={https://arxiv.org/pdf/1811.00866.pdf}
+}
+@article{xu2020automatic,
+  title={Automatic perturbation analysis for scalable certified robustness and beyond},
+  author={Xu, Kaidi and Shi, Zhouxing and Zhang, Huan and Wang, Yihan and Chang, Kai-Wei and Huang, Minlie and Kailkhura, Bhavya and Lin, Xue and Hsieh, Cho-Jui},
+  journal={Advances in Neural Information Processing Systems},
+  volume={33},
+  year={2020}
+}
+@inproceedings{xu2021fast,
+    title={{Fast and Complete}: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers},
+    author={Kaidi Xu and Huan Zhang and Shiqi Wang and Yihan Wang and Suman Jana and Xue Lin and Cho-Jui Hsieh},
+    booktitle={International Conference on Learning Representations},
+    year={2021},
+    url={https://openreview.net/forum?id=nVZtXBI6LNn}
+}
+@article{wang2021beta,
+  title={{Beta-CROWN}: Efficient bound propagation with per-neuron split constraints for complete and incomplete neural network verification},
+  author={Wang, Shiqi and Zhang, Huan and Xu, Kaidi and Lin, Xue and Jana, Suman and Hsieh, Cho-Jui and Kolter, J Zico},
+  journal={Advances in Neural Information Processing Systems},
+  volume={34},
+  year={2021}
+}
+@inproceedings{shi2024genbab,
+  title={Neural Network Verification with Branch-and-Bound for General Nonlinearities},
+  author={Shi, Zhouxing and Jin, Qirui and Kolter, Zico and Jana, Suman and Hsieh, Cho-Jui and Zhang, Huan},
+  booktitle={International Conference on Tools and Algorithms for the Construction and Analysis of Systems},
+  year={2025}
+}
+@article{zhang2022general,
+  title={General Cutting Planes for Bound-Propagation-Based Neural Network Verification},
+  author={Zhang, Huan and Wang, Shiqi and Xu, Kaidi and Li, Linyi and Li, Bo and Jana, Suman and Hsieh, Cho-Jui and Kolter, J Zico},
+  journal={Advances in Neural Information Processing Systems},
+  year={2022}
+}
+@inproceedings{zhou2024scalable,
+  title={Scalable Neural Network Verification with Branch-and-bound Inferred Cutting Planes},
+  author={Zhou, Duo and Brix, Christopher and Hanasusanto, Grani A and Zhang, Huan},
+  booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
+  year={2024}
+}