Multi-Agent Agreement problems (MAP) - the ability of a population of agents to search out and converge on a common state - are central issues in many multi-agent settings, from d...
In the paper we propose a new type of regularization procedure for training sparse Bayesian methods for classification. Transforming Hessian matrix of log-likelihood function to d...
Abstract—It is important to reduce the Optical Proximity Correction (OPC) runtime while maintaining a good result quality. In this paper, we obtain a better formula, which theore...
We introduce an alternative Lempel-Ziv text parsing, LZ-End, that converges to the entropy and in practice gets very close to LZ77. LZ-End forces sources to finish at the end of ...
We introduce a distributed adaptive estimation algorithm operating in an ideal fully connected sensor network. The algorithm estimates node-specific signals at each node based on...