We develop a framework for obtaining Fully Polynomial Time Approximation Schemes (FPTASs) for stochastic univariate dynamic programs with either convex or monotone single-period c...
Nir Halman, Diego Klabjan, Chung-Lun Li, James B. ...
We present an algorithm which provides the one-dimensional subspace where the Bayes error is minimized for the C class problem with homoscedastic Gaussian distributions. Our main ...
Online prediction methods are typically presented as serial algorithms running on a single processor. However, in the age of web-scale prediction problems, it is increasingly comm...
Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, Lin X...
We introduce a distributed adaptive estimation algorithm operating in an ideal fully connected sensor network. The algorithm estimates node-specific signals at each node based on...
Block-wise access to data is a central theme in the design of efficient external memory (EM) algorithms. A second important issue, when more than one disk is present, is fully par...
Frank K. H. A. Dehne, David A. Hutchinson, Anil Ma...