5 papers · 1 filter
Sample Complexity of Multicalibration for Multilevel Properties
Jiuyao Lu, Krishnakumar Balasubramanian, Aleksandr Podkopaev +1
Calibration requires a predictor to be unbiased after conditioning on its own predictions. Multicalibration asks for this guarantee simultaneously across a collection of groups. Ma…
MatrAIx: Simulating the World with 8.3 Billion Persona Agents
Xiaomin Li, Yuexing Hao, Jianheng Hou +90
Human evaluation of AI systems and digital products is costly, slow, and difficult to scale. Offline evaluations are more scalable but often abstract away human diversity and inter…
The Sample Complexity of Multicalibration
Natalie Collina, Jiuyao Lu, Georgy Noarov +1
We study the minimax sample complexity of multicalibration in the batch setting. A learner observes i.i.d. samples from an unknown distribution and must output a (possibly rand…
Fast Rerandomization for Balancing Covariates in Randomized Experiments: A Metropolis-Hastings Framework
Jiuyao Lu, Tianruo Zhang, Ke Zhu
Balancing covariates is critical for credible and efficient randomized experiments. Rerandomization addresses this by repeatedly generating treatment assignments until covariate ba…
Optimal Lower Bounds for Online Multicalibration
Natalie Collina, Jiuyao Lu, Georgy Noarov +1
We prove tight lower bounds for online multicalibration, establishing an information-theoretic separation from marginal calibration. In the general setting where group functions ca…