1 code implementation • 11 Dec 2023 • Ryan King, Tianbao Yang, Bobak Mortazavi
In downstream tasks, including in-hospital mortality prediction and phenotyping, our pretrained model outperforms baselines in settings where only a fraction of the data is labeled, emphasizing its ability to enhance ICU data analysis.
no code implementations • 26 Sep 2022 • Zepeng Huo, Taowei Ji, Yifei Liang, Shuai Huang, Zhangyang Wang, Xiaoning Qian, Bobak Mortazavi
We argue that traditional methods have rarely made use of both times-series dynamics of the data as well as the relatedness of the features from different sensors.
no code implementations • 31 Mar 2022 • Randy Ardywibowo, Shahin Boluki, Zhangyang Wang, Bobak Mortazavi, Shuai Huang, Xiaoning Qian
At its core is an implicit variational distribution on binary gates that are dependent on previous observations, which will select the next subset of features to observe.
no code implementations • 17 Oct 2021 • Ryan King, Bobak Mortazavi
However, many of these methods do not have a detection method for new classes or make assumptions about the distribution of classes.
1 code implementation • 6 Jun 2021 • Ziyu Jiang, Tianlong Chen, Bobak Mortazavi, Zhangyang Wang
Hence, the key innovation in SDCLR is to create a dynamic self-competitor model to contrast with the target model, which is a pruned version of the latter.
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Justin Lovelace, Bobak Mortazavi
Automated radiology report generation has the potential to reduce the time clinicians spend manually reviewing radiographs and streamline clinical care.
no code implementations • 3 Mar 2020 • Zepeng Huo, Arash Pakbin, Xiaohan Chen, Nathan Hurley, Ye Yuan, Xiaoning Qian, Zhangyang Wang, Shuai Huang, Bobak Mortazavi
Activity recognition in wearable computing faces two key challenges: i) activity characteristics may be context-dependent and change under different contexts or situations; ii) unknown contexts and activities may occur from time to time, requiring flexibility and adaptability of the algorithm.
no code implementations • 8 Jan 2019 • Randy Ardywibowo, Guang Zhao, Zhangyang Wang, Bobak Mortazavi, Shuai Huang, Xiaoning Qian
This power-efficient sensing scheme can be achieved by deciding which group of sensors to use at a given time, requiring an accurate characterization of the trade-off between sensor energy usage and the uncertainty in ignoring certain sensor signals while monitoring.