22 citations · 47 across the 9 of their papers we have counts for
6 papers · 1 filter
Correcting Performance Estimation Bias in Imbalanced Classification with Minority Subconcepts
Taylor Maxson, Roberto Corizzo, Yaning Wu +2
Class-level evaluation can conceal substantial performance disparities across subconcepts within the same class, causing models that perform well on average to fail on specific sub…
System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games
Indranil Sur, Zachary Daniels, Abrar Rahman +16
As Artificial and Robotic Systems are increasingly deployed and relied upon for real-world applications, it is important that they exhibit the ability to continually learn and adap…
On the combined effect of class imbalance and concept complexity in deep learning
Kushankur Ghosh, Colin Bellinger, Roberto Corizzo +2
Structural concept complexity, class overlap, and data scarcity are some of the most important factors influencing the performance of classifiers under class imbalance conditions.…
ReMix: Calibrated Resampling for Class Imbalance in Deep learning
Colin Bellinger, Roberto Corizzo, Nathalie Japkowicz
Class imbalance is a problem of significant importance in applied deep learning where trained models are exploited for decision support and automated decisions in critical areas su…
Independent Component Analysis for Trustworthy Cyberspace during High Impact Events: An Application to Covid-19
Zois Boukouvalas, Christine Mallinson, Evan Crothers +5
Social media has become an important communication channel during high impact events, such as the COVID-19 pandemic. As misinformation in social media can rapidly spread, creating…
Contextual One-Class Classification in Data Streams
Richard Hugh Moulton, Herna L. Viktor, Nathalie Japkowicz +1
In machine learning, the one-class classification problem occurs when training instances are only available from one class. It has been observed that making use of this class's str…