5 papers
No Free Lunch: Fundamental Limits of Learning Non-Hallucinating Generative Models
Changlong Wu, Ananth Grama, Wojciech Szpankowski
Generative models have shown impressive capabilities in synthesizing high-quality outputs across various domains. However, a persistent challenge is the occurrence of "hallucinatio…
Robust Online Classification: From Estimation to Denoising
Changlong Wu, Ananth Grama, Wojciech Szpankowski
We study online classification of features into labels with general hypothesis classes. In our setting, true labels are determined by some function within the hypothesis class but…
Prediction with eventual almost sure guarantees
Changlong Wu, Narayana Santhanam
We study the problem of sequentially predicting properties of a probabilistic model and its next outcome over an infinite horizon, with the goal of ensuring that the predictions in…
Online Distribution Learning with Local Private Constraints
Jin Sima, Changlong Wu, Olgica Milenkovic +1
We study the problem of online conditional distribution estimation with \emph{unbounded} label sets under local differential privacy. Let be a distribution-valued fun…
Oracle-Efficient Hybrid Online Learning with Unknown Distribution
Changlong Wu, Jin Sima, Wojciech Szpankowski
We study the problem of oracle-efficient hybrid online learning when the features are generated by an unknown i.i.d. process and the labels are generated adversarially. Assuming ac…