16 citations · 16 across the 6 of their papers we have counts for
6 papers
Robust Conformal CBF and CLF Controllers via Iterative Policy Updates
Omid Mirzaeedodangeh, Eliot Shekhtman, Nikolai Matni +1
Conformal prediction (CP) has been used to obtain probabilistic bounds on the error between a learned dynamics model and the true but unknown system. Such CP bounds can then be emb…
Safe Planning in Interactive Environments via Iterative Policy Updates and Adversarially Robust Conformal Prediction
Omid Mirzaeedodangeh, Eliot Shekhtman, Nikolai Matni +1
Safe planning of an autonomous agent in interactive environments -- such as the control of a self-driving vehicle among pedestrians -- poses a major challenge as the behavior of th…
Nearly Instance-Optimal Parameter Recovery from Many Trajectories via Hellinger Localization
Eliot Shekhtman, Yichen Zhou, Ingvar Ziemann +2
Learning from temporally-correlated data is a core facet of modern machine learning. Yet our understanding of sequential learning remains incomplete, particularly in the multi-traj…
Strategic Usage in a Multi-Learner Setting
Eliot Shekhtman, Sarah Dean
Real-world systems often involve some pool of users choosing between a set of services. With the increase in popularity of online learning algorithms, these services can now self-o…
Latent Diffusion for Language Generation
Justin Lovelace, Varsha Kishore, Chao Wan +2
Diffusion models have achieved great success in modeling continuous data modalities such as images, audio, and video, but have seen limited use in discrete domains such as language…
Online Missing Value Imputation and Change Point Detection with the Gaussian Copula
Yuxuan Zhao, Eric Landgrebe, Eliot Shekhtman +1
Missing value imputation is crucial for real-world data science workflows. Imputation is harder in the online setting, as it requires the imputation method itself to be able to evo…