We study online learning when individual instances are corrupted by adversarially chosen random noise. We assume the noise distribution is unknown, and may change over time with n...
Abstract--We derive eigenvalue beamformers to resolve an unknown signal of interest whose spatial signature lies in a known subspace, but whose orientation in that subspace is othe...
Ali Pezeshki, B. D. Van Veen, Louis L. Scharf, H. ...
Abstract. This paper reports on the development of a finite state system for finding grammar errors without actually specifying the error. A corpus of Swedish text written by chi...
Sylvana Sofkova Hashemi, Robin Cooper, Robert Ande...
In this paper we discuss boosting algorithms that maximize the soft margin of the produced linear combination of base hypotheses. LPBoost is the most straightforward boosting algor...
Manfred K. Warmuth, Karen A. Glocer, S. V. N. Vish...
We are concerned with the problem of sequential prediction using a givenhypothesis class of continuously-manyprediction strategies. An eectiveperformance measure is the minimax re...