7 citations · 12 across the 7 of their papers we have counts for
7 papers
climber++: Pivot-Based Approximate Similarity Search over Big Data Series
Liang Zhang, Mohamed Y. Eltabakh, Elke A. Rundensteiner +1
The generation and collection of big data series are becoming an integral part of many emerging applications in sciences, IoT, finance, and web applications among several others. T…
CoLafier: Collaborative Noisy Label Purifier With Local Intrinsic Dimensionality Guidance
Dongyu Zhang, Ruofan Hu, Elke Rundensteiner
Deep neural networks (DNNs) have advanced many machine learning tasks, but their performance is often harmed by noisy labels in real-world data. Addressing this, we introduce CoLaf…
Help or Hinder? Evaluating the Impact of Fairness Metrics and Algorithms in Visualizations for Consensus Ranking
Hilson Shrestha, Kathleen Cachel, Mallak Alkhathlan +2
For applications where multiple stakeholders provide recommendations, a fair consensus ranking must not only ensure that the preferences of rankers are well represented, but must a…
Finding Short Signals in Long Irregular Time Series with Continuous-Time Attention Policy Networks
Thomas Hartvigsen, Jidapa Thadajarassiri, Xiangnan Kong +1
Irregularly-sampled time series (ITS) are native to high-impact domains like healthcare, where measurements are collected over time at uneven intervals. However, for many classific…
Stop&Hop: Early Classification of Irregular Time Series
Thomas Hartvigsen, Walter Gerych, Jidapa Thadajarassiri +2
Early classification algorithms help users react faster to their machine learning model's predictions. Early warning systems in hospitals, for example, let clinicians improve their…
FairFuse: Interactive Visual Support for Fair Consensus Ranking
Hilson Shrestha, Kathleen Cachel, Mallak Alkhathlan +2
Fair consensus building combines the preferences of multiple rankers into a single consensus ranking, while ensuring any group defined by a protected attribute (such as race or gen…