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Abstract—In this paper, the ‘Approximate Message Passing’ (AMP) algorithm, initially developed for compressed sensing of signals under i.i.d. Gaussian measurement matrices, has been extended to a multi-terminal setting (MAMP algorithm). It has been shown t ...
There have been many studies on the spatial configuration of cities, but few attempts to quantify the difference in building patterns between the old and new parts of cities. This may be partly attributable to lack of suitable study methods. This paper pre ...
Street networks are one of the very few types of complex networks where the history of the network can be traced over long periods of time. Here we introduce methods for quantifying the geometric characteristics of street networks and analyze the details o ...
The problem of successive refinement in distributed source coding and in joint source-channel coding is considered. The emphasis is placed on the case where the sources have to be recovered losslessly in the second stage. In distributed source coding, it i ...
Generalized versions of the entropic (Hirschman-Beckner) and support (Elad-Bruckstein) uncertainty principle are presented for frames representations. Moreover, a sharpened version of the support inequality is obtained by introducing a generalization of th ...
The morphology of street patterns has been the subject of many studies in recent decades. While some have noted the textural and morphological differences in various parts of many cities, there have been few attempts to quantify the street patterns that co ...
In this paper, we propose a strategy for fusing clustering maps obtained with different remote sensing sources. Dempster- Shafer (DS) Theory is a powerful fusion method that allows to combine classifications from different sources and handles ignorance, im ...
This paper presents an information--theoretical method for weighting ensemble forecasts with new information. Weighted ensemble forecasts can be used to adjust the distribution that an existing ensemble of time series represents, without modifying the valu ...
This paper investigates the control of an ML component within the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) devoted to black-box optimization. The known CMA-ES weakness is its sample complexity, the number of evaluations of the objective fun ...
We study the distributed inference task over regression and classification models where the likelihood function is strongly log-concave. We show that diffusion strategies allow the KL divergence between two likelihood functions to converge to zero at the r ...