Stochastic Gradient Methods

• Faster non-convex federated learning via global and local momentum (arXiv)
  R. Das, A. Acharya, A. Hashemi, S. Sanghavi, I. Dhillon, U. Topcu.
  To appear in Conference on Uncertainity in Artificial Intelligence (UAI) (UAI), 2022. (Spotlight)
• Robust Training in High Dimensions via Block Coordinate Geometric Median Descent (arXiv, slides, poster, code)
  A. Acharya, A. Hashemi, P. Jain, S. Sanghavi, I. Dhillon, U. Topcu.
  In International Conference on Artificial Intelligence and Statistics (AISTATS), March 2022.
• On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Federated Learning (pdf)
  A. Hashemi, A. Acharya, R. Das, H. Vikalo, S. Sanghavi, I. Dhillon.
  IEEE Transactions on Parallel and Distributed Systems (IEEE TPDS), December 2021.
• Nomadic Computing for Big Data Analytics
  H. Yu, C. Hsieh, H. Yun, S. Vishwanathan, I. Dhillon.
  IEEE Computer (IEEE Computer) 49(4), pp. 52–60, 2016.
• NOMAD: Non-locking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion (pdf, software)
  H. Yun, H. Yu, C. Hsieh, S. Vishwanathan, I. Dhillon.
  In International Conference on Very Large Data Bases (VLDB), pp. 975-986, July 2014.