Search Results for author:
Found 4 papers, 0 papers with code
The Viability of Best-worst Scaling and Categorical Data Label Annotation Tasks in Detecting Implicit Bias
We identify several shortcomings of BWS relative to traditional categorical annotation: (1) When compared to categorical annotation, we estimate BWS takes approximately 4. 5x longer to complete; (2) BWS does not scale well to large annotation tasks with sparse target phenomena; (3) The high correlation between BWS and the traditional task shows that the benefits of BWS can be recovered from a simple categorically annotated, non-aggregated dataset.
TalkUp: Paving the Way for Understanding Empowering Language
Empowering language is important in many real-world contexts, from education to workplace dynamics to healthcare.
Improving the Performance of Stochastic Local Search for Maximum Vertex Weight Clique Problem Using Programming by Optimization
The maximum vertex weight clique problem (MVWCP) is an important generalization of the maximum clique problem (MCP) that has a wide range of real-world applications.
An Optical Frontend for a Convolutional Neural Network
The parallelism of optics and the miniaturization of optical components using nanophotonic structures, such as metasurfaces present a compelling alternative to electronic implementations of convolutional neural networks.
