publications

conference & journal articles

2024

  1. Finding MIDDLE Ground: Scalable and Secure Distributed Learning
    Marco Bornstein, Nawaf Nazir, Jan Drgona, and 2 more authors
    In Conference on Information and Knowledge Management, 2024

2023

  1. SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model Communication
    Marco Bornstein, Tahseen Rabbani, Evan Wang, and 2 more authors
    In International Conference on Learning Representations, 2023
  2. Large-Scale Distributed Learning via Private On-Device LSH
    Marco Bornstein*, Tahseen Rabbani*, and Furong Huang
    In Thirty-seventh Conference on Neural Information Processing Systems, 2023

2019

  1. Optimal nanoparticles for heat absorption and cost
    Marco Bornstein, Toni K Tullius, and Yildiz Bayazitoglu
    International Journal of Heat and Mass Transfer, 2019

preprints

2024

  1. FACT or Fiction: Can Truthful Mechanisms Eliminate Federated Free Riding?
    Marco Bornstein, Amrit Singh Bedi, Abdirisak Mohamed, and 1 more author
    2024

2023

  1. Towards Realistic Mechanisms That Incentivize Federated Participation and Contribution
    Marco Bornstein, Amrit Singh Bedi, Anit Kumar Sahu, and 2 more authors
    2023

2022

  1. Escaping From Saddle Points Using Asynchronous Coordinate Gradient Descent
    Marco Bornstein, Jin-Peng Liu, Jingling Li, and 1 more author
    arXiv preprint arXiv:2211.09908, 2022

2021

  1. Comfetch: Federated Learning of Large Networks on Memory-Constrained Clients via Sketching
    Tahseen Rabbani, Brandon Feng, Marco Bornstein, and 4 more authors
    arXiv preprint arXiv:2109.08346, 2021