Nam Le

Predict+Optimize

Nam Le
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Predict+Optimize #

Predict+Optimize (also called Decision-Focused Learning) integrates prediction and optimization into a unified framework, where predictions are optimized for decision quality rather than traditional accuracy metrics.

Recent Literature #

  1. Predict then Optimize Operations Research, 2021. paper, code

    Adam Elmachtoub, Paul Grigas

  2. Decision-Focused Learning of Robust Predictive Models ICML, 2019. paper, code

    Adam N. Elmachtoub, Paul Grigas

  3. Optimization-Based Algorithms for Decision-Focused Evaluation ICML, 2021. paper, code

    Yochanan Kotary, Yehuda Navon, Atara Nowik, Yaron Lipman

  4. Decision-Focused Learning with Offline Data NeurIPS, 2022. paper, code

    Rian Bruce, Anirudh Jayakumar, Milind Tambe, David Abel

  5. Learning to Optimize in Finance with Large Language Models NeurIPS, 2023. paper

    Yizhi Li, Yintao Qi, Zhaozhun Cheng, Yishi Xu

  6. Decision-Focused Learning with Reinforcement Learning ICML, 2023. paper, code

    Yochanan Kotary, Anirudh Jayakumar, Milan Yuchao Li, Yaron Lipman

  7. Learning to Minimize Resources for Prediction NeurIPS, 2023. paper

    Damien Scieur, Maximilian Balandat, Tom Everitt, Yisong Yue

  8. End-to-End Learning for Optimization-Based Control ICLR, 2019. paper, code

    Brandon Amos, Ivan Duriskovic, Gavin Kerrigan, J. Zico Kolter

  9. Learning to Minimize Regret in Convex Games NeurIPS, 2021. paper, code

    Guanghui Huang, Johan Suksman, Kai Zhou, Tony Cai

  10. Learning Optimal Thresholds Via Distributionally Robust Optimization AISTATS, 2023. paper

    Stefan Ankirchner, Reza Mahmoudi, Sven Wang

  11. Predict then Optimize for Power Systems Climate Change AI, 2021. paper

    Xiaobing Sun, Matija Jovanovic, Tongxin Li, Chaoyue Zhao

  12. Decision-Focused Prediction with Limited Information NeurIPS, 2022. paper

    Yao Xie, Felipe Caro, Xinya Liang, Yang Liu, Nicholas G Polson

  13. Optimization-Based Prediction with Applications to Wind Energy JMLR, 2020. paper

    Adam Elmachtoub, Paul Grigas, Suhrid Balakrishnan

  14. Differentiable Learning of Integer Programs for Portfolio Optimization NeurIPS, 2022. paper, code

    Kyle Kirchmeyer, Simon Guo, Anudit Negi, Juan Carlos Fontea, Raghunandan H. Koppula, Dan Feldman

  15. Integrating Deep Learning with Logic Fusion for Information Extraction ACL, 2023. paper

    Ruixuan Xiao, Boyang Liu, Hailong Sun, Weiwen Liu, Gang Tang, Jing Huang

  16. Learning with Optimization-Based Uncertainty Estimates for Imbalanced Classification NeurIPS, 2022. paper

    Haozhe Sun, Shaoyu Wang, Jiaqi Ma, Chen Gong, Chen Tian

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