We study the problem of active learning with convex loss functions. We prove that even under bounded noise constraints, the minimax rates for proper active learning are often no b...
Abstract--A new Bayesian model is proposed for image segmentation based upon Gaussian mixture models (GMM) with spatial smoothness constraints. This model exploits the Dirichlet co...
Christophoros Nikou, Aristidis Likas, Nikolas P. G...
Abstract. Mathematical programs (MPs) are a class of constrained optimization problems that include linear, mixed-integer, and disjunctive programs. Strategies for solving MPs rely...
Ashish Agarwal, Sooraj Bhat, Alexander Gray, Ignac...
Server consolidation through virtualization is becoming an effective way to save power and space in enterprise data centers. However, it also brings additional operational risks f...
Triggering errors in concurrent programs is a notoriously difficult task. A key reason for this is the behavioral complexity resulting from the large number of interleavings of op...