Works with * indicate alphabetical ordering of authors.


  1. WSDM
    RGRecSys: A Toolkit for Robustness Evaluation of Recommender Systems
    Zohreh Ovaisi, Shelby Heinecke, Jia Li, Yongfeng Zhang, Elena Zheleva, and Caiming Xiong
    Proceedings of the Fifthteenth ACM International Conference on Web Search and Data Mining, 2022
  2. Preprint
    Deconfounded Causal Collaborative Filtering
    Shuyuan Xu, Juntao Tan, Shelby Heinecke, Jia Li, and Yongfeng Zhang
    Preprint, 2022


  1. DCAI
    Combining Data-driven Supervision with Human-in-the-loop Feedback for Entity Resolution
    Wenpeng Yin, Shelby Heinecke, Jia Li, Nitish Keskar, Michael Jones, Shouzhong Shi, Stanislav Georgiev, Kurt Milich, Joseph Esposito, and Caiming Xiong
    Data-Centric AI Workshop at NeurIPS, 2021
  2. AAAI
    Communication-Aware Collaborative Learning*
    Avrim Blum, Shelby Heinecke, and Lev Reyzin
    Proceedings of the AAAI Conference on Artificial Intelligence, 2021


  1. Thesis
    Resilient Structures and Robust Machine Learning Algorithms
    Shelby Lynn Heinecke
    PhD Thesis, 2020


  1. HCOMP
    Crowdsourced PAC Learning under Classification Noise*
    Shelby Heinecke, and Lev Reyzin
    Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 2019


  1. Allerton
    On the Resilience of Bipartite Networks*
    Shelby Heinecke, Will Perkins, and Lev Reyzin
    In 2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2018

In Preparation

  1. In Preparation
    On Measure-Theoretic Sensitivity in the Setting of N^d Actions*
    Shelby Heinecke, Emily Wickstrom, and Cesar Silva
    In Preparation