36 citations · 65 across the 6 of their papers we have counts for
6 papers
Unknown Examples & Machine Learning Model Generalization
Yeounoh Chung, Peter J. Haas, Eli Upfal +1
Over the past decades, researchers and ML practitioners have come up with better and better ways to build, understand and improve the quality of ML models, but mostly under the key…
Automated Data Slicing for Model Validation:A Big data - AI Integration Approach
Yeounoh Chung, Tim Kraska, Neoklis Polyzotis +2
As machine learning systems become democratized, it becomes increasingly important to help users easily debug their models. However, current data tools are still primitive when it…
A Data Quality Metric (DQM): How to Estimate The Number of Undetected Errors in Data Sets
Yeounoh Chung, Sanjay Krishnan, Tim Kraska
Data cleaning, whether manual or algorithmic, is rarely perfect leaving a dataset with an unknown number of false positives and false negatives after cleaning. In many scenarios, q…
A Behavior Analysis-Based Game Bot Detection Approach Considering Various Play Styles
Yeounoh Chung, Chang-yong Park, Noo-ri Kim +4
An approach for game bot detection in MMORPGs is proposed based on the analysis of game playing behavior. Since MMORPGs are large scale games, users can play in various ways. This…
Using RDMA for Lock Management
Yeounoh Chung, Erfan Zamanian
In this work, we aim to evaluate different Distributed Lock Management service designs with Remote Direct Memory Access (RDMA). In specific, we implement and evaluate the centraliz…
Estimating the Impact of Unknown Unknowns on Aggregate Query Results
Yeounoh Chung, Michael Lind Mortensen, Carsten Binnig +1
It is common practice for data scientists to acquire and integrate disparate data sources to achieve higher quality results. But even with a perfectly cleaned and merged data set,…