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...
Different types of data skewness can result in load imbalance in the context of parallel joins under the shared nothing architecture. We study one important type of skewness, join ...
Foto N. Afrati, Victor Kyritsis, Paraskevas V. Lek...
We show that a fast algorithm for the QR factorization of a Toeplitz or Hankel matrix A is weakly stable in the sense that RT R is close to AT A. Thus, when the algorithm is used ...
Adam W. Bojanczyk, Richard P. Brent, Frank R. de H...
We present a numerical approximation technique for the analysis of continuous-time Markov chains that describe networks of biochemical reactions and play an important role in the ...
Thomas A. Henzinger, Maria Mateescu, Linar Mikeev,...
This article presents novel results concerning the recovery of signals from undersampled data in the common situation where such signals are not sparse in an orthonormal basis or ...