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This work develops a distributed optimization algorithm with guaranteed exact convergence for a broad class of left-stochastic combination policies. The resulting exact diffusion strategy is shown to have a wider stability range and superior convergence pe ...
This work develops a distributed optimization strategy with guaranteed exact convergence for a broad class of left-stochastic combination policies. The resulting exact diffusion strategy is shown in Part II to have a wider stability range and superior conv ...
With the thumb serving an important role in the function of the human hand, improving robotic prosthetic thumb functionality will have a direct impact on the prosthesis itself. So far, no significant work exists that examines the ranges of motion a prosthe ...
2013
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A methodology for plasma turbulence code validation is discussed, focusing on quantitative assessment of the agreement between experiments and simulations. The present work extends the analysis carried out in a previous paper [P. Ricci et al., Phys. Plasma ...
American Institute of Physics2011
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Part I of this work developed the exact diffusion algorithm to remove the bias that is characteristic of distributed solutions for deterministic optimization problems. The algorithm was shown to be applicable to a larger set of combination policies than ea ...
2017
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We present a survey of the first 21 years of web-based artificial life (WebAL) research and applications, broadly construed to include the many different ways in which artificial life and web technologies might intersect. Our survey covers the period from ...
Mit Press2016
The work develops a strategy for the production of ethanol from lignocellulosic biomass. In this strategy, the cellulose and hemicellulose fractions are simultaneously converted to sugars using a γ-valerolactone (GVL) solvent containing a dilute acid catal ...
The least-mean squares algorithm is non-robust against impulsive noise. Incorporating an error nonlinearity into the update equation is one useful way to mitigate the effects of impulsive noise. This work develops an adaptive structure that parametrically ...
This work develops a decentralized adaptive strategy for throughput maximization over peer-to-peer (P2P) networks. The adaptive strategy can cope with changing network topologies, is robust to network disruptions, and does not rely on central processors. T ...
Using duality arguments from optimization theory, this work develops an effective distributed gradient boosting strategy for inference and classification by networked clusters of learners. By sharing local dual variables with their immediate neighbors thro ...
