Some Recent Works in Generative Data Science
Speaker: Guang Chen (UCLA)
Abstract: This talk starts from a vision of establishing a field of "Generative Data Science," which aims to elucidates the underlying principles behind generative AI. This vision is supported by the recent observation that "creating something out of nothing" is possible and beneficial through synthetic data generation. The rest of talks focus on the initial steps towards this goal by showcasing our recent progresses in measuring fidelity (of generated image data), watermarking (on generated tabular data) and privacy auditing (of synthetic data).