publications

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2023

  1. AISTATS
    Learning to Defer to Multiple Experts: Consistent Surrogate Losses, Confidence Calibration, and Conformal Ensembles
    Verma*, Rajeev, Barrejón*, Daniel, and Nalisnick, Eric
    In to appear in the proceedings of the 26th International Conference on Artificial Intelligence and Statistics (AISTATS) 2023

2022

  1. ICML
    Calibrated Learning to Defer with One-vs-All Classifiers
    Verma, Rajeev, and Nalisnick, Eric
    In Proceedings of the 39th International Conference on Machine Learning (ICML) 2022
  2. ICML HMCaT
    On the Calibration of Learning to Defer to Multiple Experts
    Verma, Rajeev, Barrejón, Daniel, and Nalisnick, Eric
    In ICML Workshop on Human-Machine Collaboration and Teaming 2022

2021

  1. ICONIP
    Attend to Your Review: A Deep Neural Network to Extract Aspects from Peer Reviews
    Verma, Rajeev, Shinde, Kartik, Arora, Hardik, and Ghosal, Tirthankar
    In International Conference on Neural Information Processing 2021
  2. ReScience C
    [Re] Explaining Groups of Points in Low-Dimensional Representations
    Verma, Rajeev, Wagemans, J.J.O, Dahal, Paras, and Elfrink, Auke
    In ReScience C 7,2, #24 2021

2019

  1. ACL
    Deepsentipeer: Harnessing sentiment in review texts to recommend peer review decisions
    Ghosal, Tirthankar, Verma, Rajeev, Ekbal, Asif, and Bhattacharyya, Pushpak
    In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics 2019
  2. IEEE CONECCT
    Knowledge Graph Representation Learning Based Drug Informatics
    Verma, Rajeev, and Kumar, Preetam
    In 2019 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) 2019