no code implementations • 24 May 2024 • Haoze He, Juncheng Billy Li, Xuan Jiang, Heather Miller
In this work, we introduce a method for selecting sparse sub-matrices that aim to minimize the performance gap between PEFT vs. full fine-tuning (FT) while also reducing both fine-tuning computational cost and memory cost.
no code implementations • 17 May 2024 • Emin Burak Onat, Shangqing Cao, Raiyan Rizwan, Xuan Jiang, Mark Hansen, Raja Sengupta, Anjan Chakrabarty
Environmental factors pose a significant challenge to the operational efficiency and safety of advanced air mobility (AAM) networks.
no code implementations • 25 Jan 2023 • Xuan Jiang, Yuhan Tang, Zhiyi Tang, Junzhe Cao, Vishwanath Bulusu, Xin Peng, Cristian Poliziani, Raja Sengupta
Urban air mobility (UAM) has the potential to revolutionize transportation in metropolitan areas, providing a new mode of transportation that could alleviate congestion and improve accessibility.
no code implementations • 23 Dec 2021 • Xuan Jiang, Josh Everts
We used a token-wise and document-wise sentiment analysis using both unsupervised and supervised models applied to both news and user reviews dataset.
no code implementations • 10 Mar 2021 • Chen Chai, Juanwu Lu, Xuan Jiang, Xiupeng Shi, Zeng Zeng
An AutoML method based on XGBoost, termed AutoGBM, is built as the classifier for prediction and feature ranking.