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Found 8 papers, 1 papers with code
Ex-Ante Assessment of Discrimination in Dataset
Data owners face increasing liability for how the use of their data could harm under-priviliged communities.
SoFaiR: Single Shot Fair Representation Learning
To avoid discriminatory uses of their data, organizations can learn to map them into a representation that filters out information related to sensitive attributes.
Aura: Privacy-preserving Augmentation to Improve Test Set Diversity in Speech Enhancement
Noise suppression models running in production environments are commonly trained on publicly available datasets.
Fair Representations by Compression
Organizations that collect and sell data face increasing scrutiny for the discriminatory use of data.
Learning Smooth and Fair Representations
Organizations that own data face increasing legal liability for its discriminatory use against protected demographic groups, extending to contractual transactions involving third parties access and use of the data.
Probabilistic Super-Resolution of Solar Magnetograms: Generating Many Explanations and Measuring Uncertainties
Machine learning techniques have been successfully applied to super-resolution tasks on natural images where visually pleasing results are sufficient.
Single-Frame Super-Resolution of Solar Magnetograms: Investigating Physics-Based Metrics \& Losses
Breakthroughs in our understanding of physical phenomena have traditionally followed improvements in instrumentation.
Multi-Differential Fairness Auditor for Black Box Classifiers
Machine learning algorithms are increasingly involved in sensitive decision-making process with adversarial implications on individuals.
