3 accepted papers
Modern foundation models are evaluated through broad capabilities such as arithmetic, reasoning, safety, and robustness, yet it remains unclear in a principled sense when *finite tests* can meaningfully certify such claims. We develop a rigorous theory of capability evaluation by formalizing evaluat…
We study the problem of online conditional distribution estimation with \emph{unbounded} label sets under local differential privacy. The problem may be succinctly stated as follows. Let $\mathcal{F}$ be a distribution-valued function class with an unbounded label set. Our aim is to estimate an \emp…
Federated clustering (FC) is an unsupervised learning problem that arises in a number of practical applications, including personalized recommender and healthcare systems. With the adoption of recent laws ensuring the "right to be forgotten", the problem of machine unlearning for FC methods has beco…