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Graph Vulnerability and Robustness: A Survey
The study of network robustness is a critical tool in the characterizati...
05/02/2021 ∙ by Scott Freitas, et al. ∙
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EnergyVis: Interactively Tracking and Exploring Energy Consumption for ML Models
The advent of larger machine learning (ML) models have improved state-of...
03/30/2021 ∙ by Omar Shaikh, et al. ∙
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MalNet: A Large-Scale Cybersecurity Image Database of Malicious Software
Computer vision is playing an increasingly important role in automated m...
01/31/2021 ∙ by Scott Freitas, et al. ∙
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A Large-Scale Database for Graph Representation Learning
With the rapid emergence of graph representation learning, the construct...
11/16/2020 ∙ by Scott Freitas, et al. ∙
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Argo Lite: Open-Source Interactive Graph Exploration and Visualization in Browsers
Graph data have become increasingly common. Visualizing them helps peopl...
08/26/2020 ∙ by Siwei Li, et al. ∙
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ELF: An Early-Exiting Framework for Long-Tailed Classification
The natural world often follows a long-tailed data distribution where on...
06/22/2020 ∙ by Rahul Duggal, et al. ∙
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Evaluating Graph Vulnerability and Robustness using TIGER
The study of network robustness is a critical tool in the characterizati...
06/10/2020 ∙ by Scott Freitas, et al. ∙
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UnMask: Adversarial Detection and Defense Through Robust Feature Alignment
Deep learning models are being integrated into a wide range of high-impa...
02/21/2020 ∙ by Scott Freitas, et al. ∙
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REST: Robust and Efficient Neural Networks for Sleep Monitoring in the Wild
In recent years, significant attention has been devoted towards integrat...
01/29/2020 ∙ by Rahul Duggal, et al. ∙
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Local Partition in Rich Graphs
Local graph partitioning is a key graph mining tool that allows research...
03/14/2018 ∙ by Scott Freitas, et al. ∙
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