Publications

  1. [C12] TabSketchFM: Sketch-based Tabular Representation Learning for Data Discovery over Data Lakes,* Joint first-authors
    Aamod Khatiwada*, Harsha Kokel*, Ibrahim Abdelaziz, Subhajit Chaudhury, Julian Dolby, Oktie Hassanzadeh, Zhenhan Huang, Tejaswini Pedapati, Horst Samulowitz, Kavitha Srinivas, In ICDE 2024.
    paper
  2. [P2] ACPBench: Reasoning about Action, Change, and Planning (Preprint),
    Harsha Kokel, Michael Katz, Kavitha Srinivas, Shirin Sohrabi, In ArXiv 2024.
    paper | blog | code
  3. [C11] Thought of Search: Planning with Language Models Through The Lens of Efficiency,
    Michael Katz, Harsha Kokel, Kavitha Srinivas, Shirin Sohrabi, In NeurIPS 2024.
    paper
  4. [W10] Automating Thought of Search: A Journey Towards Soundness and Completeness,
    Daniel Cao, Michael Katz, Harsha Kokel, Kavitha Srinivas, Shirin Sohrabi, In OWA Workshop at NeurIPS 2024.
    paper
  5. [W9] TabSketchFM: Sketch-based Tabular Representation Learning for Data Discovery over Data Lakes,* Joint first-authors
    Aamod Khatiwada*, Harsha Kokel*, Ibrahim Abdelaziz, Subhajit Chaudhury, Julian Dolby, Oktie Hassanzadeh, Zhenhan Huang, Tejaswini Pedapati, Horst Samulowitz, Kavitha Srinivas, In Tabular Representation Learning Workshop at NeurIPS 2024.
    paper
  6. [W8] Planning with Language Models Through The Lens of Efficiency,
    Michael Katz, Harsha Kokel, Kavitha Srinivas, Shirin Sohrabi, In Planning and RL (PRL) Workshop at ICAPS 2024.
    paper
  7. [W7] Guiding Hiearchical Reinforcement Learning in Partially Observable Environments with AI Planning ,
    Brandon Rozek, Michael Katz, Harsha Kokel, Kavitha Srinivas, Shirin Sohrabi, In Planning and RL (PRL) Workshop at ICAPS 2024.
    paper
  8. [C10] Large Language Models as Planning Domain Generators,
    James Oswald, Kavitha Srinivas, Harsha Kokel, Junkyu Lee, Michael Katz, Shirin Sohrabi, In ICAPS 2024.
    paper | code | DOI
  9. [A3] Partially Observable Hierarchical Reinforcement Learning with AI Planning (Student Abstract),
    Brandon Rozek, Junkyu Lee, Harsha Kokel, Michael Katz, Shirin Sohrabi, In AAAI 2024.
    paper
  10. [A2] Large Language Models as Planning Domain Generators (Student Abstract),
    James Oswald, Kavitha Srinivas, Harsha Kokel, Junkyu Lee, Michael Katz, Shirin Sohrabi, In AAAI 2024.
    paper
  11. [W6] Learning Parameterized Policies for Planning Annotated RL,
    Harsha Kokel, Junkyu Lee, Michael Katz, Shirin Sohrabi, In Planning and RL (PRL) Workshop at IJCAI 2023.
    paper
  12. [C9] Action Space Reduction for Planning Domains,
    Harsha Kokel, Junkyu Lee, Michael Katz, Kavitha Srinivas, Shirin Sohrabi, In IJCAI 2023.
    paper | blog | code | DOI| video | cite
    @inproceedings{KokelLKSS23,
       title={Action Space Reduction for Planning Domains},
       author={Kokel, Harsha and Lee, Junkyu and Katz, Michael and Srinivas, Kavitha and Sohrabi, Shirin},
       publisher={International Joint Conferences on Artificial Intelligence Organization},
       pages = {5394--5401},
       year = {2023},
       month = {8},
       doi = {10.24963/ijcai.2023/599} booktitle = {Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, {IJCAI-23}},
       }
  13. [P1] LakeBench: Benchmarks for Data Discovery over Data Lakes (Preprint),
    Kavitha Srinivas, Julian Dolby, Ibrahim Abdelaziz, Oktie Hassanzadeh, Harsha Kokel, Aamod Khatiwada, Tejaswini Pedapati, Subhajit Chaudhury, Horst Samulowitz, In ArXiv 2023.
    paper | code | video
  14. [J1] RePReL: A Unified Framework for Integrating Relational Planning and Reinforcement Learning for Effective Abstraction in Discrete and Continuous Domains,
    Harsha Kokel, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli, In Neural Computing and Applications 2022.
    paper | DOI | cite
    @article{KokelNRT22,
       author={Harsha Kokel and Sriraam Natarajan and Balaraman Ravindran and Prasad Tadepalli},
       journal={Neural Computing and Applications},
       title={RePReL: a unified framework for integrating relational planning and reinforcement learning for effective abstraction in discrete and continuous domains},
       year={2022},
       doi={https://doi.org/10.1007/s00521-022-08119-y},
       }
  15. [C8] LARA -- Human-guided collaborative problem solver: Effective integration of learning, reasoning and communication,
    Harsha Kokel, Mayukh Das, Rakibul Islam, Julia Bonn, Jon Cai, Soham Dan, Anjali Narayan-Chen, Prashant Jayannavar, Janardhan Rao Doppa, Julia Hockenmaier, Sriraam Natarajan, Martha Palmer, Dan Roth, In The Tenth Annual Conference on Advances in Cognitive Systems (ACS) 2022.
    paper | blog | supplemental | video | cite
    @article{KokeletalACS22,
       title={LARA -- Human-guided collaborative problem solver: Effective integration of learning, reasoning and communication},
       author={Harsha Kokel, Mayukh Das, Rakibul Islam, Julia Bonn, Jon Cai, Soham Dan, Anjali Narayan-Chen, Prashant Jayannavar, Janardhan Rao Doppa, Julia Hockenmaier, Sriraam Natarajan, Martha Palmer, Dan Roth},
       journal={The Tenth Annual Conference on Advances in Cognitive Systems (ACS)},
       year={2022},
       }
  16. [C7] ORIENT: Submodular Mutual Information Measures for Data Subset Selection under Distribution Shift,* equal contributions
    Athresh Karanam*, Krishnateja Killamsetty*, Harsha Kokel*, Rishabh K Iyer, In NeurIPS 2022.
    paper | code | supplemental | DOI | cite
    @inproceedings{KaranamKKI22,
       author = {Athresh Karanam and Krishnateja Killamsetty and Harsha Kokel and Rishabh K Iyer},
       title = {{ORIENT}: Submodular Mutual Information Measures for Data Subset Selection under Distribution Shift},
       year = {2022},
       booktitle = {NeurIPS},
       }
  17. [C6] Hybrid Deep RePReL: Integrating Relational Planning and Reinforcement Learning for Information Fusion,
    Harsha Kokel, Nikhilesh Prabhakar, Balaraman Ravindran, Eric Blasch, Prasad Tadepalli, Sriraam Natarajan, In IEEE 25th International Conference on Information Fusion (FUSION) 2022.
    paper | blog | slide | DOI| video | cite
    @inproceedings{KokelPRBTN22,
       title={Hybrid Deep RePReL: Integrating Relational Planning and Reinforcement Learning for Information Fusion},
       author={Harsha Kokel and Nikhilesh Prabhakar and Balaraman Ravindran and Eric Blasch and Prasad Tadepalli and Sriraam Natarajan},
       journal={IEEE 25th International Conference on Information Fusion (FUSION)},
       year={2022},
       doi={https://doi.org/10.23919/FUSION49751.2022.9841246},
       }
  18. [W5] Action Space Reduction for Planning Domains,
    Harsha Kokel, Junkyu Lee, Michael Katz, Shirin Sohrabi, Kavitha Srinivas, In Planning and RL (PRL) Workshop at ICAPS 2022.
    paper | slide | video
  19. [A2] Dynamic probabilistic logic models for effective task-specific abstractions in RL (Abstract),
    Harsha Kokel, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli, In 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM) 2022.
    paper | code | poster
  20. [A1] How to Reduce Action Space for Planning Domains? (Student Abstract),* oral presentation (20/111 accepted abstracts)
    Harsha Kokel, Junkyu Lee, Michael Katz, Shirin Sohrabi, Kavitha Srinivas, In AAAI 2022.
    paper | DOI| video | cite
    @article{KokelLKSS22,
       title={How to Reduce Action Space for Planning Domains? (Student Abstract)},
       author={Kokel, Harsha and Lee, Junkyu and Katz, Michael and Sohrabi, Shirin and Srinivas, Kavitha},
       journal={AAAI},
       pages={12989--12990},
       year={2022},
       url={https://ojs.aaai.org/index.php/AAAI/article/view/21631},
       }
  21. [W4] Deep RePReL-Combining Planning and Deep RL for acting in relational domains,
    Harsha Kokel, Arjun Manoharan, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli, In Deep RL Workshop at NeurIPS 2021.
    paper | code | supplemental | slide | video | cite
    @article{KokelMNBTDRL,
       title={Deep RePReL-Combining Planning and Deep RL for acting in relational domains},
       author={Kokel, Harsha and Manoharan, Arjun and Natarajan, Sriraam and Ravindran, Balaraman and Tadepalli, Prasad},
       journal={Deep {RL} Workshop at {NeurIPS}},
       year={2021},
       }
  22. [W3] Dynamic probabilistic logic models for effective abstractions in RL,
    Harsha Kokel, Arjun Manoharan, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli, In Statistical Relational AI (StarAI) Workshop at IJCLR 2021.
    paper | poster | cite
    @article{KokelMNBTSTARAI,
       title={Dynamic probabilistic logic models for effective abstractions in RL},
       author={Kokel, Harsha and Manoharan, Arjun and Natarajan, Sriraam and Ravindran, Balaraman and Tadepalli, Prasad},
       journal = {CoRR},
       volume = {abs/2110.08318},
       year={2021},
       }
  23. [C5] Human-guided Collaborative Problem Solving: A Natural Language based Framework,
    Harsha Kokel, Mayukh Das, Rakibul Islam, Julia Bonn, Jon Cai, Soham Dan, Anjali Narayan-Chen, Prashant Jayannavar, Janardhan Rao Doppa, Julia Hockenmaier, Sriraam Natarajan, Martha Palmer, Dan Roth, In ICAPS (demo track) 2021.
    paper | blog | video | cite
    @article{KokeletalDemo,
       title={Human-guided Collaborative Problem Solving: A Natural Language based Framework},
       author={Harsha Kokel, Mayukh Das, Rakibul Islam, Julia Bonn, Jon Cai, Soham Dan, Anjali Narayan-Chen, Prashant Jayannavar, Janardhan Rao Doppa, Julia Hockenmaier, Sriraam Natarajan, Martha Palmer, Dan Roth},
       journal={Thirty First International Conference on Automated Planning and Scheduling ({ICAPS}) Demo Track},
       year={2021},
       }
  24. [W2] RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction (Extended Abstract),* contributed talk (11/25 accepted paper)
    Harsha Kokel, Arjun Manoharan, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli, In Planning and RL (PRL) Workshop at ICAPS 2021.
    paper | poster | video
  25. [C4] A Probabilistic Approach to Extract Qualitative Knowledge for Early Prediction of Gestational Diabetes,
    Athresh Karanam, Alexander L. Hayes, Harsha Kokel, David M. Haas, Predrag Radivojac, Sriraam Natarajan, In AIME 2021.
    paper | blog | DOI| video | cite
    @inproceedings{KaranamHKHRN21,
       author = {Athresh Karanam and Alexander L. Hayes and Harsha Kokel and David M. Haas and Predrag Radivojac and Sriraam Natarajan},
       title = {A Probabilistic Approach to Extract Qualitative Knowledge for Early Prediction of Gestational Diabetes},
       year = {2021},
       publisher = {Springer International Publishing},
       pages = {497--502},
       booktitle = {Artificial Intelligence in Medicine},
       isbn = {978-3-030-77211-6},
       DOI = {10.1007/978-3-030-77211-6_59},
       }
  26. [C3] RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction,
    Harsha Kokel, Arjun Manoharan, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli, In ICAPS 2021.
    paper | blog | code | supplemental | DOI| video | cite
    @article{KokelMNRT21,
       title={RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction},
       author={Kokel, Harsha and Manoharan, Arjun and Natarajan, Sriraam and Balaraman, Ravindran and Tadepalli, Prasad},
       journal={Proceedings of the International Conference on Automated Planning and Scheduling},
       number={1},
       volume={31},
       year={2021},
       month={May},
       pages={533--541},
       url={https://ojs.aaai.org/index.php/ICAPS/article/view/16001},
       }
  27. [W1] Graph Sparsification via Meta-Learning,* contributed talk (4/22 accepted paper)
    Guihong Wan, Harsha Kokel, In Deep Learning for Graphs (DLG) Workshop at AAAI 2021.
    paper | slide | video | cite
    @article{WanK21,
       title={Graph Sparsification via Meta-Learning},
       author={Wan, Guihong and Kokel, Harsha},
       journal={Deep Learning for Graphs (DLG) Workshop at AAAI},
       year={2021}
       }
  28. [C2] A Unified Framework for Knowledge Intensive Gradient Boosting: Leveraging Human Experts for Noisy Sparse Domain,
    Harsha Kokel, Phillip Odom, Shuo Yang, Sriraam Natarajan, In AAAI 2020.
    paper | blog | code | supplemental | poster | slide | DOI | cite
    @article{KokelOYN20,
       author = {Harsha Kokel and Phillip Odom and Shuo Yang and Sriraam Natarajan},
       title = {A Unified Framework for Knowledge Intensive Gradient Boosting: Leveraging Human Experts for Noisy Sparse Domains},
       journal = {Proceedings of the AAAI Conference on Artificial Intelligence}
       volume = {34},
       number = {04},
       pages = {4460--4468},
       year = {2020},
       month = {Apr.},
       DOI = {10.1609/aaai.v34i04.5873},
       url = {https://aaai.org/ojs/index.php/AAAI/article/view/5873},
       }
  29. [C1] Morpheme Extraction Task,
    Rashmi Sankepally, Komal Agarwal, Harsha Kokel, Prasenjit Majumder, In Forum for Information Retrieval Evaluation (FIRE) 2013.
    paper | DOI | cite
    @inproceedings{SankepallyKAM13,
       author = {Rashmi Sankepally and Harsha Kokel and Komal Agarwal and Prasenjit Majumder},
       title = {Morpheme Extraction Task at {FIRE} 2012-2013},
       booktitle = {Proceedings of the Forum on Information Retrieval Evaluation, {FIRE}},
       pages = {5:1--5:4},
       publisher = {{ACM}},
       year = {2013},
       url = {https://doi.org/10.1145/2701336.2701637},
       doi = {10.1145/2701336.2701637},
       }