@article{einstein,
author =       "Albert Einstein",
title =        "{Zur Elektrodynamik bewegter Körper}",
journal =      "Annalen der Physik",
volume =       "322",
number =       "10",
pages =        "891--921",
year =         "1905"}

@book{latexcompanion,
author    = "Michel Goossens and Frank Mittelbach and Alexander Samarin",
title     = "The \LaTeX\ Companion",
year      = "1993",
publisher = "Addison-Wesley"}

@inproceedings{finn2016guided,
  title={Guided cost learning: Deep inverse optimal control via policy optimization},
  author={Finn, Chelsea and Levine, Sergey and Abbeel, Pieter},
  booktitle={International conference on machine learning},
  pages={49--58},
  year={2016},
  organization={PMLR}
}

@article{bellman1966dynamic,
	title={Dynamic programming},
	author={Bellman, Richard},
	journal={Science},
	volume={153},
	number={3731},
	pages={34--37},
	year={1966},
	publisher={American Association for the Advancement of Science}
}

@inproceedings{ziebart2008maximum,
	title={Maximum entropy inverse reinforcement learning.},
	author={Ziebart, Brian D and Maas, Andrew L and Bagnell, J Andrew and Dey, Anind K and others},
	booktitle={Aaai},
	volume={8},
	pages={1433--1438},
	year={2008},
	organization={Chicago, IL, USA}
}

@article{nguyen2015inverse,
	title={Inverse reinforcement learning with locally consistent reward functions},
	author={Nguyen, Quoc Phong and Low, Bryan Kian Hsiang and Jaillet, Patrick},
	journal={Advances in neural information processing systems},
	volume={28},
	year={2015}
}

@inproceedings{ziebart2008navigate,
	title={Navigate like a cabbie: Probabilistic reasoning from observed context-aware behavior},
	author={Ziebart, Brian D and Maas, Andrew L and Dey, Anind K and Bagnell, J Andrew},
	booktitle={Proceedings of the 10th international conference on Ubiquitous computing},
	pages={322--331},
	year={2008}
}

@inproceedings{NEURIPS2021_83a368f5,
	author = {Abbas, Ahmed and Swoboda, Paul},
	booktitle = {Advances in Neural Information Processing Systems},
	editor = {M. Ranzato and A. Beygelzimer and Y. Dauphin and P.S. Liang and J. Wortman Vaughan},
	pages = {15635--15649},
	publisher = {Curran Associates, Inc.},
	title = {Combinatorial Optimization for Panoptic Segmentation: A Fully Differentiable Approach},
	volume = {34},
	year = {2021}
}

@article{bell1982regret,
	title={Regret in decision making under uncertainty},
	author={Bell, David E},
	journal={Operations research},
	volume={30},
	number={5},
	pages={961--981},
	year={1982},
	publisher={Informs}
}

@article{loomes1982regret,
	title={Regret theory: An alternative theory of rational choice under uncertainty},
	author={Loomes, Graham and Sugden, Robert},
	journal={The economic journal},
	volume={92},
	number={368},
	pages={805--824},
	year={1982},
	publisher={Oxford University Press Oxford, UK}
}

@book{birge2011introduction,
	title={Introduction to stochastic programming},
	author={Birge, John R and Louveaux, Francois},
	year={2011},
	publisher={Springer Science \& Business Media}
}

@article{donti2017task,
	title={Task-based end-to-end model learning in stochastic optimization},
	author={Donti, Priya and Amos, Brandon and Kolter, J Zico},
	journal={Advances in neural information processing systems},
	volume={30},
	year={2017}
}


@InProceedings{pmlr-v70-amos17a,
	title = 	 {{O}pt{N}et: Differentiable Optimization as a Layer in Neural Networks},
	author =       {Brandon Amos and J. Zico Kolter},
	booktitle = 	 {Proceedings of the 34th International Conference on Machine Learning},
	pages = 	 {136--145},
	year = 	 {2017},
	editor = 	 {Precup, Doina and Teh, Yee Whye},
	volume = 	 {70},
	series = 	 {Proceedings of Machine Learning Research},
	month = 	 {06--11 Aug},
	publisher =    {PMLR},
	pdf = 	 {http://proceedings.mlr.press/v70/amos17a/amos17a.pdf},
	url = 	 {https://proceedings.mlr.press/v70/amos17a.html},
}

@article{berthet2020learning,
	title={Learning with differentiable pertubed optimizers},
	author={Berthet, Quentin and Blondel, Mathieu and Teboul, Olivier and Cuturi, Marco and Vert, Jean-Philippe and Bach, Francis},
	journal={Advances in neural information processing systems},
	volume={33},
	pages={9508--9519},
	year={2020}
}

@inproceedings{wilder2018melding,
	title={Melding the data-decisions pipeline: Decision-focused learning for combinatorial optimization},
	author={Wilder, Bryan and Dilkina, Bistra and Tambe, Milind},
	booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
	volume={33},
	number={01},
	pages={1658--1665},
	year={2019}
}

@article{agrawal2019differentiating,
	title={Differentiating through a cone program},
	author={Agrawal, Akshay and Barratt, Shane and Boyd, Stephen and Busseti, Enzo and Moursi, Walaa M},
	journal={arXiv preprint arXiv:1904.09043},
	year={2019}
}

@techreport{froehlich2008route,
	title={Route prediction from trip observations},
	author={Froehlich, Jon and Krumm, John},
	year={2008},
	institution={SAE Technical Paper}
}

@inproceedings{henry2010learning,
	title={Learning to navigate through crowded environments},
	author={Henry, Peter and Vollmer, Christian and Ferris, Brian and Fox, Dieter},
	booktitle={2010 IEEE international conference on robotics and automation},
	pages={981--986},
	year={2010},
	organization={IEEE}
}

@inproceedings{vasquez2014inverse,
	title={Inverse reinforcement learning algorithms and features for robot navigation in crowds: an experimental comparison},
	author={Vasquez, Dizan and Okal, Billy and Arras, Kai O},
	booktitle={2014 IEEE/RSJ International Conference on Intelligent Robots and Systems},
	pages={1341--1346},
	year={2014},
	organization={IEEE}
}

@inproceedings{ziebart2008navigate,
	title={Navigate like a cabbie: Probabilistic reasoning from observed context-aware behavior},
	author={Ziebart, Brian D and Maas, Andrew L and Dey, Anind K and Bagnell, J Andrew},
	booktitle={Proceedings of the 10th international conference on Ubiquitous computing},
	pages={322--331},
	year={2008}
}

@@data{c7j010-22,
	title={Cabspotting Dataset},
	doi = {10.15783/C7J010},
	url = {https://dx.doi.org/10.15783/C7J010},
	author = {Piorkowski, Michal and Sarafijanovic-Djukic, Natasa and Grossglauser, Matthias },
	publisher = {IEEE Dataport},
	title = {CRAWDAD epfl/mobility},
	year = {2009} }


@article{fernando2020deep,
	title={Deep inverse reinforcement learning for behavior prediction in autonomous driving: Accurate forecasts of vehicle motion},
	author={Fernando, Tharindu and Denman, Simon and Sridharan, Sridha and Fookes, Clinton},
	journal={IEEE Signal Processing Magazine},
	volume={38},
	number={1},
	pages={87--96},
	year={2020},
	publisher={IEEE}
}

@ARTICLE{9307325,
	author={Fernando, Tharindu and Denman, Simon and Sridharan, Sridha and Fookes, Clinton},
	journal={IEEE Signal Processing Magazine}, 
	title={Deep Inverse Reinforcement Learning for Behavior Prediction in Autonomous Driving: Accurate Forecasts of Vehicle Motion}, 
	year={2021},
	volume={38},
	number={1},
	pages={87-96},
	keywords={Deep learning;Navigation;Supervised learning;Decision making;Focusing;Reinforcement learning;Autonomous vehicles},
	doi={10.1109/MSP.2020.2988287}}


@article{wulfmeier2017large,
	title={Large-scale cost function learning for path planning using deep inverse reinforcement learning},
	author={Wulfmeier, Markus and Rao, Dushyant and Wang, Dominic Zeng and Ondruska, Peter and Posner, Ingmar},
	journal={The International Journal of Robotics Research},
	volume={36},
	number={10},
	pages={1073--1087},
	year={2017},
	publisher={SAGE Publications Sage UK: London, England}
}

@InProceedings{Demirovic2019AnII,
	author="Demirovi{\'{c}}, Emir
	and Stuckey, Peter J.
	and Bailey, James
	and Chan, Jeffrey
	and Leckie, Chris
	and Ramamohanarao, Kotagiri
	and Guns, Tias",
	editor="Rousseau, Louis-Martin
	and Stergiou, Kostas",
	title="An Investigation into Prediction + Optimisation for the Knapsack Problem",
	booktitle="Integration of Constraint Programming, Artificial Intelligence, and Operations Research",
	year="2019",
	publisher="Springer International Publishing",
	address="Cham",
	pages="241--257"
}

@article{burton1992instance,
  title={On an instance of the inverse shortest paths problem},
  author={Burton, Didier and Toint, Ph L},
  journal={Mathematical programming},
  volume={53},
  pages={45--61},
  year={1992},
  publisher={Springer}
}

@article{yang1999two,
	title={Two general methods for inverse optimization problems},
	author={Yang, C and Zhang, J},
	journal={Applied Mathematics Letters},
	volume={12},
	number={2},
	pages={69--72},
	year={1999},
	publisher={Elsevier}
}

@article{wang2009cutting,
	title={Cutting plane algorithms for the inverse mixed integer linear programming problem},
	author={Wang, Lizhi},
	journal={Operations research letters},
	volume={37},
	number={2},
	pages={114--116},
	year={2009},
	publisher={Elsevier}
}

@article{ahuja2001inverse,
	title={Inverse optimization},
	author={Ahuja, Ravindra K and Orlin, James B},
	journal={Operations research},
	volume={49},
	number={5},
	pages={771--783},
	year={2001},
	publisher={INFORMS}
}

@article{aswani2018inverse,
	title={Inverse optimization with noisy data},
	author={Aswani, Anil and Shen, Zuo-Jun and Siddiq, Auyon},
	journal={Operations Research},
	volume={66},
	number={3},
	pages={870--892},
	year={2018},
	publisher={INFORMS}
}

@article{chan2020inverse,
	title={Inverse optimization for the recovery of constraint parameters},
	author={Chan, Timothy CY and Kaw, Neal},
	journal={European Journal of Operational Research},
	volume={282},
	number={2},
	pages={415--427},
	year={2020},
	publisher={Elsevier}
}




@inproceedings{ng2000algorithms,
	title={Algorithms for inverse reinforcement learning.},
	author={Ng, Andrew Y and Russell, Stuart and others},
	booktitle={Icml},
	volume={1},
	pages={2},
	year={2000}
}

@article{arora2021survey,
	title={A survey of inverse reinforcement learning: Challenges, methods and progress},
	author={Arora, Saurabh and Doshi, Prashant},
	journal={Artificial Intelligence},
	volume={297},
	pages={103500},
	year={2021},
	publisher={Elsevier}
}


@inproceedings{tan2019deep,
	title={Deep inverse optimization},
	author={Tan, Yingcong and Delong, Andrew and Terekhov, Daria},
	booktitle={Integration of Constraint Programming, Artificial Intelligence, and Operations Research: 16th International Conference, CPAIOR 2019, Thessaloniki, Greece, June 4--7, 2019, Proceedings 16},
	pages={540--556},
	year={2019},
	organization={Springer}
}

@article{gupta2022decomposition,
	title={Decomposition and adaptive sampling for data-driven inverse linear optimization},
	author={Gupta, Rishabh and Zhang, Qi},
	journal={INFORMS Journal on Computing},
	volume={34},
	number={5},
	pages={2720--2735},
	year={2022},
	publisher={INFORMS}
}

@inproceedings{barmann2017emulating,
	title={Emulating the expert: Inverse optimization through online learning},
	author={B{\"a}rmann, Andreas and Pokutta, Sebastian and Schneider, Oskar},
	booktitle={International Conference on Machine Learning},
	pages={400--410},
	year={2017},
	organization={PMLR}
}

@article{tan2020learning,
	title={Learning linear programs from optimal decisions},
	author={Tan, Yingcong and Terekhov, Daria and Delong, Andrew},
	journal={Advances in Neural Information Processing Systems},
	volume={33},
	pages={19738--19749},
	year={2020}
}

@article{mohajerin2018data,
	title={Data-driven inverse optimization with imperfect information},
	author={Mohajerin Esfahani, Peyman and Shafieezadeh-Abadeh, Soroosh and Hanasusanto, Grani A and Kuhn, Daniel},
	journal={Mathematical Programming},
	volume={167},
	pages={191--234},
	year={2018},
	publisher={Springer}
}




@article{niculae2017regularized,
	title={A regularized framework for sparse and structured neural attention},
	author={Niculae, Vlad and Blondel, Mathieu},
	journal={Advances in neural information processing systems},
	volume={30},
	year={2017}
}

@inproceedings{mensch2018differentiable,
	title={Differentiable dynamic programming for structured prediction and attention},
	author={Mensch, Arthur and Blondel, Mathieu},
	booktitle={International Conference on Machine Learning},
	pages={3462--3471},
	year={2018},
	organization={PMLR}
}

@inproceedings{hirakawa2018survey,
	title={Survey on vision-based path prediction},
	author={Hirakawa, Tsubasa and Yamashita, Takayoshi and Tamaki, Toru and Fujiyoshi, Hironobu},
	booktitle={Distributed, Ambient and Pervasive Interactions: Technologies and Contexts: 6th International Conference, DAPI 2018, Held as Part of HCI International 2018, Las Vegas, NV, USA, July 15--20, 2018, Proceedings, Part II 6},
	pages={48--64},
	year={2018},
	organization={Springer}
}

@inproceedings{alahi2016social,
	title={Social lstm: Human trajectory prediction in crowded spaces},
	author={Alahi, Alexandre and Goel, Kratarth and Ramanathan, Vignesh and Robicquet, Alexandre and Fei-Fei, Li and Savarese, Silvio},
	booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
	pages={961--971},
	year={2016}
}

@article{rossi2019modelling,
	title={Modelling taxi drivers’ behaviour for the next destination prediction},
	author={Rossi, Alberto and Barlacchi, Gianni and Bianchini, Monica and Lepri, Bruno},
	journal={IEEE Transactions on Intelligent Transportation Systems},
	volume={21},
	number={7},
	pages={2980--2989},
	year={2019},
	publisher={IEEE}
}

@article{gao2018optimize,
	title={Optimize taxi driving strategies based on reinforcement learning},
	author={Gao, Yong and Jiang, Dan and Xu, Yan},
	journal={International Journal of Geographical Information Science},
	volume={32},
	number={8},
	pages={1677--1696},
	year={2018},
	publisher={Taylor \& Francis}
}

@inproceedings{xiong2018predicting,
	title={Predicting traffic congestion propagation patterns: A propagation graph approach},
	author={Xiong, Haoyi and Vahedian, Amin and Zhou, Xun and Li, Yanhua and Luo, Jun},
	booktitle={Proceedings of the 11th ACM SIGSPATIAL International Workshop on computational transportation science},
	pages={60--69},
	year={2018}
}

@article{li2016t,
	title={T-DesP: Destination prediction based on big trajectory data},
	author={Li, Xiang and Li, Mengting and Gong, Yue-Jiao and Zhang, Xing-Lin and Yin, Jian},
	journal={IEEE Transactions on Intelligent Transportation Systems},
	volume={17},
	number={8},
	pages={2344--2354},
	year={2016},
	publisher={IEEE}
}

@inproceedings{ebel2020destination,
	title={Destination prediction based on partial trajectory data},
	author={Ebel, Patrick and G{\"o}l, Ibrahim Emre and Lingenfelder, Christoph and Vogelsang, Andreas},
	booktitle={2020 IEEE Intelligent Vehicles Symposium (IV)},
	pages={1149--1155},
	year={2020},
	organization={IEEE}
}

@article{liang2021nettraj,
	title={Nettraj: A network-based vehicle trajectory prediction model with directional representation and spatiotemporal attention mechanisms},
	author={Liang, Yuebing and Zhao, Zhan},
	journal={IEEE Transactions on Intelligent Transportation Systems},
	volume={23},
	number={9},
	pages={14470--14481},
	year={2021},
	publisher={IEEE}
}

@article{liang2014real,
	title={Real-time urban traffic amount prediction models for dynamic route guidance systems},
	author={Liang, Zilu and Wakahara, Yasushi},
	journal={EURASIP Journal on Wireless Communications and Networking},
	volume={2014},
	number={1},
	pages={1--13},
	year={2014},
	publisher={SpringerOpen}
}

@inproceedings{amos2019optnet,
	title={Optnet: Differentiable optimization as a layer in neural networks},
	author={Amos, Brandon and Kolter, J Zico},
	booktitle={International Conference on Machine Learning},
	pages={136--145},
	year={2017},
	organization={PMLR}
}

@inproceedings{cristian2023end,
	title={End-to-end learning for optimization via constraint-enforcing approximators},
	author={Cristian, Rares and Harsha, Pavithra and Perakis, Georgia and Quanz, Brian L and Spantidakis, Ioannis},
	booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
	volume={37},
	number={6},
	pages={7253--7260},
	year={2023}
}

@article{tang2022pyepo,
	title={Pyepo: A pytorch-based end-to-end predict-then-optimize library for linear and integer programming},
	author={Tang, Bo and Khalil, Elias B},
	journal={arXiv preprint arXiv:2206.14234},
	year={2022}
}

@inproceedings{ferber2019mipaal,
	title={Mipaal: Mixed integer program as a layer},
	author={Ferber, Aaron and Wilder, Bryan and Dilkina, Bistra and Tambe, Milind},
	booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
	volume={34},
	number={02},
	pages={1504--1511},
	year={2020}
}

@inproceedings{ruan2011distance,
	title={Distance preserving graph simplification},
	author={Ruan, Ning and Jin, Ruoming and Huang, Yan},
	booktitle={2011 IEEE 11th International Conference on Data Mining},
	pages={1200--1205},
	year={2011},
	organization={IEEE}
}

@article{nesterov2005smooth,
	title={Smooth minimization of non-smooth functions},
	author={Nesterov, Yu},
	journal={Mathematical programming},
	volume={103},
	pages={127--152},
	year={2005},
	publisher={Springer}
}

@article{floyd1962algorithm,
	title={Algorithm 97: shortest path},
	author={Floyd, Robert W},
	journal={Communications of the ACM},
	volume={5},
	number={6},
	pages={345},
	year={1962},
	publisher={ACM New York, NY, USA}
}


@inproceedings{vlastelica2019differentiation,
	title={Differentiation of blackbox combinatorial solvers},
	author={Pogan{\v{c}}i{\'c}, Marin Vlastelica and Paulus, Anselm and Musil, Vit and Martius, Georg and Rolinek, Michal},
	booktitle={International Conference on Learning Representations},
	year={2020}
}
