We design and analyze interacting online algorithms for multitask classification that perform better than independent learners whenever the tasks are related in a certain sense. W...
1 The low-SNR capacity of M-ary PSK transmission over both the additive white Gaussian noise (AWGN) and fading channels is analyzed when hard-decision detection is employed at the ...
Abstract-- We study the convergence rate of average consensus algorithms in networks with stochastic communication failures. We show how the system dynamics can be modeled by a dis...
We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...