An Exact Quantized Decentralized Gradient Descent Algorithm
We consider the problem of decentralized consensus optimization, where the sum of n smooth and strongly convex functions are minimized over…
Read moreWe consider the problem of decentralized consensus optimization, where the sum of n smooth and strongly convex functions are minimized over…
Read moreThis paper studies resilient distributed estimation under measurement attacks. A set of agents each makes successive local, linear, noisy…
Read moreThe problem of detecting a high-dimensional signal based on compressive measurements in the presence of an eavesdropper (Eve) is studied in this…
Read moreThe topic of sequence design has received considerable attention due to its wide applications in active sensing. One important desired property for…
Read moreThis paper considers and analyzes the performance of semiblind, training, and data-aided channel estimation schemes for multiple-input multiple…
Read moreIn this paper, we study blind channel-and-signal estimation by exploiting the burst-sparse structure of angular-domain propagation channels in…
Read moreLinear data-detection algorithms that build on zero forcing (ZF) or linear minimum mean-square error (L-MMSE) equalization achieve near-optimal…
Read moreIn this paper, we study the problem of beam alignment for millimeter wave (mmWave) communications, where a hybrid analog and digital beamforming…
Read moreSequential Monte Carlo (SMC) methods comprise one of the most successful approaches to approximate Bayesian filtering. However, SMC without a good…
Read moreThe paper derives the stability bound of the initial mean-square deviation of an adaptive filtering algorithm based on minimizing the 2 L th moment…
Read more