Interactive Machine Learning: From Theory to Scale

📝 Original Info

• Title: Interactive Machine Learning: From Theory to Scale
• ArXiv ID: 2512.23924
• Date: 2025-12-30
• Authors: Yinglun Zhu

📝 Abstract

First and foremost, I would like to express my deepest gratitude to my Ph.D. advisor Robert D. Nowak, for his continuous mentoring, support, and encouragement. Rob gives me great freedom to explore topics I am interested in, but at the same time, he is always passionate about discussing research problems with me and helping me get out of trouble. Rob has been everything I could ask for as an advisor. Rob is also a role model to me, as a researcher and mentor, who will keep motivating me in my future academic career. I had a wonderful summer intern at Microsoft Research NYC in 2021, where I was fortunate to be mentored by Dylan J. Foster, John Langford, and Paul Mineiro. I am extremely grateful to their mentoring; they not only taught me how to approach difficult research problems, but also spent their time helping me sharpen my presentation and communication skills.

📄 Full Content

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