Various efforts ([?, ?, ?]) have been made in recent years to derandomize probabilistic algorithms using the complexity theoretic assumption that there exists a problem in E = dti...
Russell Impagliazzo, Ronen Shaltiel, Avi Wigderson
This paper presents a case study of numerical simulations in an easy-to-use matrix computation framework named Simple Interface for Library Collections (SILC), which allows users t...
We study the problem of learning a kernel which minimizes a regularization error functional such as that used in regularization networks or support vector machines. We consider thi...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
Abstract. In this paper, we discuss approximation spaces in a granular computing framework. Such approximation spaces generalise the approaches to concept approximation existing in...
We initiate the study of on-line metric embeddings. In such an embedding we are given a sequence of n points X = x1, . . . , xn one by one, from a metric space M = (X, D). Our goal...
Piotr Indyk, Avner Magen, Anastasios Sidiropoulos,...