11 citations · 23 across the 8 of their papers we have counts for
8 papers
Efficient Backdoor Removal Through Natural Gradient Fine-tuning
Nazmul Karim, Abdullah Al Arafat, Umar Khalid +2
The success of a deep neural network (DNN) heavily relies on the details of the training scheme; e.g., training data, architectures, hyper-parameters, etc. Recent backdoor attacks…
Optimizing Real-Time Performances for Timed-Loop Racing under F1TENTH
Nitish Gupta, Kurt Wilson, Zhishan Guo
Motion planning and control in autonomous car racing are one of the most challenging and safety-critical tasks due to high speed and dynamism. The lower-level control nodes are exp…
GLARE: A Dataset for Traffic Sign Detection in Sun Glare
Nicholas Gray, Megan Moraes, Jiang Bian +6
Real-time machine learning object detection algorithms are often found within autonomous vehicle technology and depend on quality datasets. It is essential that these algorithms wo…
Protoformer: Embedding Prototypes for Transformers
Ashkan Farhangi, Ning Sui, Nan Hua +3
Transformers have been widely applied in text classification. Unfortunately, real-world data contain anomalies and noisy labels that cause challenges for state-of-art Transformers.…
A Novel Deep Learning Model for Hotel Demand and Revenue Prediction amid COVID-19
Ashkan Farhangi, Arthur Huang, Zhishan Guo
The COVID-19 pandemic has significantly impacted the tourism and hospitality sector. Public policies such as travel restrictions and stay-at-home orders had significantly affected…
An Improved Speedup Factor for Sporadic Tasks with Constrained Deadlines under Dynamic Priority Scheduling
Xin Han, Liang Zhao, Zhishan Guo +1
Schedulability is a fundamental problem in real-time scheduling, but it has to be approximated due to the intrinsic computational hardness. As the most popular algorithm for decidi…
DRESS: Dynamic RESource-reservation Scheme for Congested Data-intensive Computing Platforms
Ying Mao, Victoria Green, Jiayin Wang +2
In the past few years, we have envisioned an increasing number of businesses start driving by big data analytics, such as Amazon recommendations and Google Advertisements. At the b…
FWDA: a Fast Wishart Discriminant Analysis with its Application to Electronic Health Records Data Classification
Haoyi Xiong, Wei Cheng, Wenqing Hu +2
Linear Discriminant Analysis (LDA) on Electronic Health Records (EHR) data is widely-used for early detection of diseases. Classical LDA for EHR data classification, however, suffe…