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This book is a collection of the accepted papers presented at the Workshop on Artificial Intelligence with Biased or Scarce Data (AIBSD) in conjunction with the 36th AAAI Conference on Artificial Intelligence 2022. During AIBSD 2022, the attendees addressed the existing issues of data bias and scarcity in Artificial Intelligence and discussed potential solutions in real-world scenarios. A set of papers presented at AIBSD 2022 is selected for further publication and included in this book.
This book is included in DOAB.
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Keywords
- bias detection
- contextualized embeddings
- contrastive learning
- coresets
- deep learning
- face-recognition models
- facial attributes
- fairness
- Forecasting
- gender bias
- History of engineering & technology
- Natural Language Processing
- noisy labels
- optimization
- out-of-distribution generalization
- permutation equivariance
- robustness
- social bias
- supervised contrastive learning
- Technology, engineering, agriculture
- Technology: general issues
- temporal bias
- transfer learning
Links
DOI: 10.3390/books978-3-0365-4682-7Editions