no code implementations • 11 Nov 2022 • Harsh Patel, Nicole Schneider, Hanan Samet
Visualizations such as bar charts, scatter plots, and objects on geographical maps often convey critical information, including exact and relative numeric values, using shapes.
no code implementations • 10 Nov 2022 • Brian Ondov, Harsh B. Patel, Ai-Te Kuo, Hanan Samet, John Kastner, Yunheng Han, Hong Wei, Niklas Elmqvist
While participants preferred using the latter two dashboards to perform queries with only a geospatial component or only a temporal component, participants uniformly preferred CoronaViz for queries with both spatial and temporal components, highlighting the utility of a unified spatiotemporal encoding.
no code implementations • 28 Feb 2020 • John Kastner, Hanan Samet, Hong Wei
With the rapid continuing spread of COVID-19, it is clearly important to be able to track the progress of the virus over time in order to be better prepared to anticipate its emergence and spread in new regions as well as declines in its presence in regions thereby leading to or justifying "reopening" decisions.
no code implementations • NeurIPS 2017 • Hao Li, Soham De, Zheng Xu, Christoph Studer, Hanan Samet, Tom Goldstein
Currently, deep neural networks are deployed on low-power portable devices by first training a full-precision model using powerful hardware, and then deriving a corresponding low-precision model for efficient inference on such systems.
21 code implementations • 31 Aug 2016 • Hao Li, Asim Kadav, Igor Durdanovic, Hanan Samet, Hans Peter Graf
However, magnitude-based pruning of weights reduces a significant number of parameters from the fully connected layers and may not adequately reduce the computation costs in the convolutional layers due to irregular sparsity in the pruned networks.
Ranked #1 on Network Pruning on ImageNet