Writing deterministic programs is often difficult for problems whose optimal solutions depend on unpredictable properties of the programs’ inputs. Difficulty is also encounter...
We propose the hierarchical Dirichlet process (HDP), a nonparametric Bayesian model for clustering problems involving multiple groups of data. Each group of data is modeled with a...
Yee Whye Teh, Michael I. Jordan, Matthew J. Beal, ...
We study generalized bootstrapped confidence regions for the mean of a random vector whose coordinates have an unknown dependence structure, with a non-asymptotic control of the co...
This paper describes a general quantum lower bounding technique for the communication complexity of a function that depends on the inputs given to two parties connected via paths,...
In an errors-in-variables (EIV) model, all the measurements are corrupted by noise. The class of EIV models with constraints separable into the product of two nonlinear functions, ...