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    A comparison of two estimators for solutions to greedy algorithm in scheduling depletable sources

    , Article International Conference on Risk Management and Engineering Management, Toronto, ON, 18 April 2008 through 18 April 2008 ; 2008 , Pages 80-85 ; 9780978348458 (ISBN) Kianfar, S ; Azizi, E ; Kianfar, F ; Sharif University of Technology
    2008
    Abstract
    There are many depletable resource planning problems associated with convex cost function. The Greedy algorithm has been used to find the optimal solution for such problems. But exploiting that algorithm requires a large bulk of computations to find the optimal solution. Thus, in this paper we have established two piecewise linear estimators for the convex cost function: an inner intersection of the function values and an outer tangent. A practical experiment was conducted to compare the performance of the two presented estimators and it was observed that the outer tangent performs more efficiently than the inner intersection. The execution time of the Greedy Algorithm and the estimation... 

    Modified joint channel-and-data estimation for one-bit massive MIMO

    , Article 53rd IEEE International Symposium on Circuits and Systems, ISCAS 2021, 22 May 2021 through 28 May 2021 ; Volume 2021-May , 2021 ; 02714310 (ISSN); 9781728192017 (ISBN) Bahari, M ; Rasoulinezhad, Ramin ; Amiri, M ; Gilani, F ; Saadatnejad, S ; Nezamalhosseini, A. R ; Shabany, M ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2021
    Abstract
    Centralized and cloud computing-based network architectures are the promising tracks of future communication systems where a large scale compute power can be virtualized for various algorithms. These architectures rely on high-performance communication links between the base stations and the central computing systems. On the other hand, massive Multiple-Input Multiple-Output (MIMO) technology is a promising solution for base stations toward higher spectral efficiency. To reduce system complexity and energy consumption, 1-bit analog-to-digital converters (ADCs) are leveraged with the cost of lowering the signal quality. To recover the lost information, more sophisticated algorithms, like... 

    A distributed density estimation algorithm and its application to naive Bayes classification

    , Article Applied Soft Computing ; Volume 98 , 2021 ; 15684946 (ISSN) Khajenezhad, A ; Bashiri, M. A ; Beigy, H ; Sharif University of Technology
    Elsevier Ltd  2021
    Abstract
    We consider the problem of learning a density function from observations of an unknown underlying model in a distributed setting, where the observations are partitioned into different sites. Applying commonly used density estimation methods such as Gaussian Mixture Model (GMM) or Kernel Density Estimation (KDE) to distributed data leads to an extensive amount of communication. A familiar approach to address this issue is to sample a small subset of data and collect them into a central node to run the density estimation algorithms on them. In this paper, we follow an alternative to the sub-sampling approach by proposing the nested Log-Poly model. This model provides an accurate density...