In the next UAI research meeting on October 26th 9pm – 10pm GMT-4 (October 27th 9am – 10am Beijing time), Dr. Qian Li is scheduled to present his work.
Since this next meeting will take place at a different time than usual, we recommend referring to a timezone converter if you are interested in joining. We will use the regular meets link (also in the UAI calendar‘s description).
Bio
Dr. Qian Li is a research scientist at the Shenzhen Research Institute of Big Data (SRIBD). He previously worked as an assistant professor at the Institute of Computing Technology (ICT) Chinese Academy of Sciences, where he also earned his PhD in 2018 under the guidance of Prof. Xiaoming Sun.
He describes himself as having broad interests spanning theoretical computer science (including computational complexity, quantum computing, algorithm design and analysis), machine learning and artificial intelligence.
Abstract
In this upcoming session, Dr. Qian Li will discuss his work on approximate MDL (Minimum Description Length), which will appear at NeurIPS 2026. He will also discuss his newer work, which studies whether the prediction performance of Bayesian and Solomonoff induction remains robust under approximate log-loss minimization.
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