1 citations · 1 across the 6 of their papers we have counts for
4 papers · 1 filter
Deep Active Learning in the Open World
Tian Xie, Jifan Zhang, Haoyue Bai +1
Machine learning models deployed in open-world scenarios often encounter unfamiliar conditions and perform poorly in unanticipated situations. As AI systems advance and find applic…
AHA: Human-Assisted Out-of-Distribution Generalization and Detection
Haoyue Bai, Jifan Zhang, Robert Nowak
Modern machine learning models deployed often encounter distribution shifts in real-world applications, manifesting as covariate or semantic out-of-distribution (OOD) shifts. These…
Out-of-Distribution Learning with Human Feedback
Haoyue Bai, Xuefeng Du, Katie Rainey +2
Out-of-distribution (OOD) learning often relies heavily on statistical approaches or predefined assumptions about OOD data distributions, hindering their efficacy in addressing mul…
HYPO: Hyperspherical Out-of-Distribution Generalization
Haoyue Bai, Yifei Ming, Julian Katz-Samuels +1
Out-of-distribution (OOD) generalization is critical for machine learning models deployed in the real world. However, achieving this can be fundamentally challenging, as it require…