14 citations · 15 across the 4 of their papers we have counts for
5 papers
Deep-Learning-Assisted Highly-Accurate COVID-19 Diagnosis on Lung Computed Tomography Images
Yinuo Wang, Juhyun Bae, Ka Ho Chow +2
COVID-19 is a severe and acute viral disease that can cause symptoms consistent with pneumonia in which inflammation is caused in the alveolous regions of the lungs leading to a bu…
RDMAbox : Optimizing RDMA for Memory Intensive Workloads
Juhyun Bae, Ling Liu, Yanzhao Wu +2
We present RDMAbox, a set of low level RDMA optimizations that provide better performance than previous approaches. The optimizations are packaged in easy-to-use kernel and user sp…
Promoting High Diversity Ensemble Learning with EnsembleBench
Yanzhao Wu, Ling Liu, Zhongwei Xie +3
Ensemble learning is gaining renewed interests in recent years. This paper presents EnsembleBench, a holistic framework for evaluating and recommending high diversity and high accu…
Efficient Orchestration of Host and Remote Shared Memory for Memory Intensive Workloads
Juhyun Bae, Gong Su, Arun Iyengar +2
Since very few contributions to the development of an unified memory orchestration framework for efficient management of both host and remote idle memory have been made, we present…
Demystifying Learning Rate Policies for High Accuracy Training of Deep Neural Networks
Yanzhao Wu, Ling Liu, Juhyun Bae +6
Learning Rate (LR) is an important hyper-parameter to tune for effective training of deep neural networks (DNNs). Even for the baseline of a constant learning rate, it is non-trivi…