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...
A protocol for computing a functionality is secure if an adversary in this protocol cannot cause more harm than in an ideal computation where parties give their inputs to a truste...
We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
We consider the question of how much information can be stored by labeling the vertices of a connected undirected graph G using a constant-size set of labels, when isomorphic label...
Dana Angluin, James Aspnes, Rida A. Bazzi, Jiang C...
For statistical timing and power analysis that are very important problems in the sub-100nm technologies, stochastic analysis of power grids that characterizes the voltage fluctua...
Praveen Ghanta, Sarma B. K. Vrudhula, Sarvesh Bhar...