Cloud computing, social networking and information networks (for search, news feeds, etc) are driving interest in the deployment of large data centers. TCP is the dominant Layer 3...
Mohammad Alizadeh, Adel Javanmard, Balaji Prabhaka...
This paper introduces mirrored sampling into evolution strategies (ESs) with weighted multi-recombination. Two further heuristics are introduced: pairwise selection selects at mos...
Proportionate-type affine projection algorithms (PAPAs) are very attractive choices for echo cancellation. These algorithms combine the good features (convergence and tracking) o...
Constantin Paleologu, Jacob Benesty, Felix Albu, S...
In this paper, we analyze a general multiple-microphone and singleloudspeaker system, where an adaptive algorithm is used to cancel acoustic feedback/echo and a beamformer process...
—Dual descent methods are commonly used to solve network optimization problems because their implementation can be distributed through the network. However, their convergence rat...
Michael Zargham, A. Ribeiro, Ali Jadbabaie, Asuman...
Distributed averaging describes a class of network algorithms for the decentralized computation of aggregate statistics. Initially, each node has a scalar data value, and the goal...
This paper presents a linear high-order distributed average consensus (DAC) algorithm for wireless sensor networks. The average consensus property and convergence rate of the high...
Abstract: We propose a first-order interior-point method for linearly constrained smooth optimization that unifies and extends first-order affine-scaling method and replicator d...
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...
The asymptotic behavior of stochastic gradient algorithms is studied. Relying on some results of differential geometry (Lojasiewicz gradient inequality), the almost sure pointconve...