4 papers
LoDAdaC: a unified local training-based decentralized framework with adaptive gradients and compressed communication
Wei Liu, Anweshit Panda, Ujwal Pandey +5
In the decentralized distributed learning, achieving fast convergence and low communication cost is essential for scalability and high efficiency. Adaptive gradient methods, such a…
Anonymized Network Sensing using C++26 std::execution on GPUs
Michael Mandulak, Sayan Ghosh, S M Ferdous +2
Large-scale network sensing plays a vital role in network traffic analysis and characterization. As network packet data grows increasingly large, parallel methods have become mains…
Compressed Decentralized Momentum Stochastic Gradient Methods for Nonconvex Optimization
Wei Liu, Anweshit Panda, Ujwal Pandey +6
In this paper, we design two compressed decentralized algorithms for solving nonconvex stochastic optimization under two different scenarios. Both algorithms adopt a momentum techn…
ApproxJoin: Approximate Matching for Efficient Verification in Fuzzy Set Similarity Join
Michael Mandulak, S M Ferdous, Sayan Ghosh +2
The set similarity join problem is a fundamental problem in data processing and discovery, relying on exact similarity measures between sets. In the presence of alterations, such a…