4 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.RO2023
LESS-Map: Lightweight and Evolving Semantic Map in Parking Lots for Long-term Self-Localization
Mingrui Liu, Xinyang Tang, Yeqiang Qian +2
Precise and long-term stable localization is essential in parking lots for tasks like autonomous driving or autonomous valet parking, \textit{etc}. Existing methods rely on a fixed…
cs.LG2022★ 4 cited
Robustness to Unbounded Smoothness of Generalized SignSGD
Michael Crawshaw, Mingrui Liu, Francesco Orabona +2
Traditional analyses in non-convex optimization typically rely on the smoothness assumption, namely requiring the gradients to be Lipschitz. However, recent evidence shows that thi…
cs.LG2022★ 3 cited
Fast Composite Optimization and Statistical Recovery in Federated Learning
Yajie Bao, Michael Crawshaw, Shan Luo +1
As a prevalent distributed learning paradigm, Federated Learning (FL) trains a global model on a massive amount of devices with infrequent communication. This paper investigates a…