14 citations · 23 across the 10 of their papers we have counts for
10 papers
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…
MANI-Rank: Multiple Attribute and Intersectional Group Fairness for Consensus Ranking
Kathleen Cachel, Elke Rundensteiner, Lane Harrison
Combining the preferences of many rankers into one single consensus ranking is critical for consequential applications from hiring and admissions to lending. While group fairness h…
One-Shot Learning on Attributed Sequences
Zhongfang Zhuang, Xiangnan Kong, Elke Rundensteiner +2
One-shot learning has become an important research topic in the last decade with many real-world applications. The goal of one-shot learning is to classify unlabeled instances when…
To Share, or not to Share Online Event Trend Aggregation Over Bursty Event Streams
Olga Poppe, Chuan Lei, Lei Ma +2
Complex event processing (CEP) systems continuously evaluate large workloads of pattern queries under tight time constraints. Event trend aggregation queries with Kleene patterns a…
MLAS: Metric Learning on Attributed Sequences
Zhongfang Zhuang, Xiangnan Kong, Elke Rundensteiner +2
Distance metric learning has attracted much attention in recent years, where the goal is to learn a distance metric based on user feedback. Conventional approaches to metric learni…
Sharon: Shared Online Event Sequence Aggregation
Olga Poppe, Allison Rozet, Chuan Lei +2
Streaming systems evaluate massive workloads of event sequence aggregation queries. State-of-the-art approaches suffer from long delays caused by not sharing intermediate results o…
GRETA: Graph-based Real-time Event Trend Aggregation
Olga Poppe, Chuan Lei, Elke A. Rundensteiner +1
Streaming applications from algorithmic trading to traffic management deploy Kleene patterns to detect and aggregate arbitrarily-long event sequences, called event trends. State-of…
Event Trend Aggregation Under Rich Event Matching Semantics
Olga Poppe, Chuan Lei, Elke A. Rundensteiner +1
Streaming applications from health care analytics to algorithmic trading deploy Kleene queries to detect and aggregate event trends. Rich event matching semantics determine how to…
Attributed Sequence Embedding
Zhongfang Zhuang, Xiangnan Kong, Elke Rundensteiner +2
Mining tasks over sequential data, such as clickstreams and gene sequences, require a careful design of embeddings usable by learning algorithms. Recent research in feature learnin…
Summarization and Matching of Density-Based Clusters in Streaming Environments
Di Yang, Elke A. Rundensteiner, Matthew O. Ward
Density-based cluster mining is known to serve a broad range of applications ranging from stock trade analysis to moving object monitoring. Although methods for efficient extractio…