no code implementations • 21 Nov 2023 • Prashant Khanduri, Chengyin Li, Rafi Ibn Sultan, Yao Qiang, Joerg Kliewer, Dongxiao Zhu
A key novelty of our work is to develop solution accuracy-independent algorithms that do not require large batch gradients (and function evaluations) for solving federated CO problems.
1 code implementation • 19 Nov 2023 • Rafi Ibn Sultan, Chengyin Li, Hui Zhu, Prashant Khanduri, Marco Brocanelli, Dongxiao Zhu
The Segment Anything Model (SAM) has shown impressive performance when applied to natural image segmentation.
1 code implementation • 14 Sep 2023 • Yao Qiang, Chengyin Li, Prashant Khanduri, Dongxiao Zhu
Furthermore, if ViTs are not properly trained with the given data and do not prioritize the region of interest, the {\it post hoc} methods would be less effective.
no code implementations • 28 Aug 2023 • Chengyin Li, Prashant Khanduri, Yao Qiang, Rafi Ibn Sultan, Indrin Chetty, Dongxiao Zhu
In addition to the domain gaps between natural and medical images, disparities in the spatial arrangement between 2D and 3D images, the substantial computational burden imposed by powerful GPU servers, and the time-consuming manual prompt generation impede the extension of SAM to a broader spectrum of medical image segmentation applications.
no code implementations • 31 Jan 2023 • Yao Qiang, Chengyin Li, Prashant Khanduri, Dongxiao Zhu
Importantly, our DSA framework leads to improved fairness guarantees over prior works on multiple prediction tasks without compromising target prediction performance.
1 code implementation • 17 Jan 2023 • Xin Li, Deng Pan, Chengyin Li, Yao Qiang, Dongxiao Zhu
There are increasing demands for understanding deep neural networks' (DNNs) behavior spurred by growing security and/or transparency concerns.
1 code implementation • 23 Oct 2022 • Chengyin Li, Zheng Dong, Nathan Fisher, Dongxiao Zhu
Electric Vehicle (EV) charging recommendation that both accommodates user preference and adapts to the ever-changing external environment arises as a cost-effective strategy to alleviate the range anxiety of private EV drivers.
1 code implementation • 6 Oct 2022 • Chengyin Li, Yao Qiang, Rafi Ibn Sultan, Hassan Bagher-Ebadian, Prashant Khanduri, Indrin J. Chetty, Dongxiao Zhu
Computed Tomography (CT) based precise prostate segmentation for treatment planning is challenging due to (1) the unclear boundary of the prostate derived from CT's poor soft tissue contrast and (2) the limitation of convolutional neural network-based models in capturing long-range global context.
no code implementations • 9 Sep 2022 • Xin Li, Yao Qiang, Chengyin Li, Sijia Liu, Dongxiao Zhu
We hypothesize that adversarial training can eliminate shortcut features whereas saliency guided training can filter out non-relevant features; both are nuisance features accounting for the performance degradation on OOD test sets.
1 code implementation • 6 Apr 2020 • Xin Li, Chengyin Li, Dongxiao Zhu
We design and implement a novel three-player knowledge transfer and distillation (KTD) framework including a pre-trained attending physician (AP) network that extracts CXR imaging features from a large scale of lung disease CXR images, a fine-tuned resident fellow (RF) network that learns the essential CXR imaging features to discriminate COVID-19 from pneumonia and/or normal cases with a small amount of COVID-19 cases, and a trained lightweight medical student (MS) network to perform on-device COVID-19 patient triage and follow-up.