% Key papers for Stochastic shortest path (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2020_near_38493,
  title = {{Near-optimal Regret Bounds for Stochastic Shortest Path}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6432},
}

@inproceedings{icml2020_no_38509,
  title = {{No-Regret Exploration in Goal-Oriented Reinforcement Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/5969},
}

@inproceedings{icml2021_finding_39352,
  title = {{Finding the Stochastic Shortest Path with Low Regret: the Adversarial Cost and Unknown Transition Case}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/10629},
}

@inproceedings{neurips2021_minimax_62231,
  title = {{Minimax Regret for Stochastic Shortest Path}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28795},
}

@inproceedings{neurips2021_stochastic_62712,
  title = {{Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27550},
}

@inproceedings{neurips2021_implicit_63110,
  title = {{Implicit Finite-Horizon Approximation and Efficient Optimal Algorithms for Stochastic Shortest Path}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26372},
}

@inproceedings{icml2022_regret_41074,
  title = {{Regret Bounds for Stochastic Shortest Path Problems with Linear Function Approximation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/16385},
}

@inproceedings{icml2022_learning_40764,
  title = {{Learning Stochastic Shortest Path with Linear Function Approximation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/16867},
}

@inproceedings{icml2022_improved_40682,
  title = {{Improved No-Regret Algorithms for Stochastic Shortest Path with Linear MDP}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/16969},
}

@inproceedings{icml2023_nearly_42241,
  title = {{Nearly Minimax Optimal Regret for Learning Linear Mixture Stochastic Shortest Path}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/24287},
}

@inproceedings{neurips2026_opsrl_94202,
  title = {{OPSRL-SSP: Optimistic Posterior Sampling for Stochastic Shortest Path with Minimax-Optimal Regret}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/149166},
}