Anmol Kabra

selected papers

* equal contributions

1. The Limitations of Model Retraining in the Face of Performativity

   Anmol Kabra*,  and Kumar Kshitij Patel*

   ICML Workshop on Humans, Algorithmic Decision-Making and Society (2024).

   paper bibtex

   @inproceedings{2024kabra_limitations_retraining,
     title = {The Limitations of Model Retraining in the Face of Performativity},
     author = {Kabra*, Anmol and Patel*, Kumar Kshitij},
     booktitle = {ICML Workshop on Humans, Algorithmic Decision-Making and Society},
     year = {2024},
   }

2. Score Design for Multi-Criteria Incentivization

   Anmol Kabra, Mina Karzand, Tosca Lechner, Nathan Srebro,  and Serena Wang

   Foundations of Responsible Computing (FORC) (2024).

   paper bibtex poster

   @inproceedings{2024kabra_FORC_score_design,
     title = {Score Design for Multi-Criteria Incentivization},
     author = {Kabra, Anmol and Karzand, Mina and Lechner, Tosca and Srebro, Nathan and Wang, Serena},
     booktitle = {5th Symposium on Foundations of Responsible Computing (FORC)},
     year = {2024},
   }

3. Domain Private Transformers for Multi-Domain Dialog Systems

   Anmol Kabra,  and Ethan R. Elenberg

   Findings-EMNLP (2023).

   paper bibtex poster

   @inproceedings{2023kabra_domain_privacy,
     title = {Domain Private Transformers for Multi-Domain Dialog Systems},
     author = {Kabra, Anmol and Elenberg, Ethan R.},
     booktitle = {Findings of the Association for Computational Linguistics: EMNLP},
     year = {2023},
   }

4. Exponential Family Model-Based Reinforcement Learning via Score Matching

   Gene Li, Junbo Li,  Anmol Kabra, Nathan Srebro, Zhaoran Wang,  and Zhuoran Yang

   NeurIPS (2022). (Oral presentation).

   paper bibtex code poster

   @inproceedings{2022li_score_matching,
     title = {Exponential Family Model-Based Reinforcement Learning via Score Matching},
     author = {Li, Gene and Li, Junbo and Kabra, Anmol and Srebro, Nathan and Wang, Zhaoran and Yang, Zhuoran},
     booktitle = {Advances in Neural Information Processing Systems},
     volume = {35},
     pages = {28474--28487},
     year = {2022},
   }

5. Characterizing the Loss Landscape in Non-Negative Matrix Factorization

   Johan Bjorck,  Anmol Kabra, Kilian Q. Weinberger,  and Carla P. Gomes

   AAAI (2021).

   paper bibtex

   @inproceedings{2021bjorck_nmf,
     title = {Characterizing the Loss Landscape in Non-Negative Matrix Factorization},
     author = {Bjorck, Johan and Kabra, Anmol and Weinberger, Kilian Q. and Gomes, Carla P.},
     booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
     volume = {35},
     number = {8},
     pages = {6768--6776},
     year = {2021},
     doi = {10.1609/aaai.v35i8.16836},
     url = {https://doi.org/10.1609/aaai.v35i8.16836},
   }

6. GPU-Accelerated Principal-Agent Game for Scalable Citizen Science

   Anmol Kabra, Yexiang Xue,  and Carla P. Gomes

   COMPASS (2019).

   paper bibtex code poster slides video

   @inproceedings{2019kabra_avicaching,
     author = {Kabra, Anmol and Xue, Yexiang and Gomes, Carla P.},
     title = {GPU-Accelerated Principal-Agent Game for Scalable Citizen Science},
     year = {2019},
     isbn = {9781450367141},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     url = {https://doi.org/10.1145/3314344.3332495},
     doi = {10.1145/3314344.3332495},
     booktitle = {Proceedings of the 2nd ACM SIGCAS Conference on Computing and Sustainable Societies},
     pages = {165–173},
     numpages = {9},
     keywords = {parallel computation, mixed-integer programming, machine learning, computational sustainability, citizen science},
     location = {Accra, Ghana},
     series = {COMPASS ’19},
   }