Universal kernels have been shown to play an important role in the achievability of the Bayes risk by many kernel-based algorithms that include binary classification, regression, ...
Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. ...
Following a suggestion of Briegel, we show that a variant of the oneway model where one only allows X and Y one qubit measurements is approximately universal with respect to unita...
The strongest well-known measure for the quality of a universal hash-function family H is its being -strongly universal, which measures, for randomly chosen h H, one's inabi...
Solomonoff completed the Bayesian framework by providing a rigorous, unique, formal, and universal choice for the model class and the prior. We discuss in breadth how and in which...
Motivated by applications of rateless coding, decision feedback, and automatic repeat request (ARQ), we study the problem of universal decoding for unknown channels in the presence...
We survey the emerging area of compression-based, parameter-free, similarity distance measures useful in data-mining, pattern recognition, learning and automatic semantics extracti...
Given a universe U of n elements and a weighted collection S of m subsets of U, the universal set cover problem is to a-priori map each element u ∈ U to a set S(u) ∈ S contain...
We show that universal routing can be achieved with low overhead in distributed networks. The validity of our results rests on a new network called the fat-stack. We show that fro...