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Ali H. Sayed

Bio: Ali H. Sayed is an academic researcher from École Polytechnique Fédérale de Lausanne. The author has contributed to research in topics: Adaptive filter & Optimization problem. The author has an hindex of 81, co-authored 728 publications receiving 36030 citations. Previous affiliations of Ali H. Sayed include Harbin Engineering University & University of California, Los Angeles.


Papers
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Journal ArticleDOI
TL;DR: Under supplementary finite-dimensionality conditions, a so-called generalized Schur algorithm can be used to prove the main result concerning time-variant displacement equations with positive solutions in a general operatorial setting.
Abstract: A general result is proven concerning time-variant displacement equations with positive solutions in a general operatorial setting. It is then shown that the solutions of several completion problems, recently considered in connection with classical interpolation and moment theory, follow as special cases of the main result. The main purpose of this paper is to show that under supplementary finite-dimensionality conditions, a so-called generalized Schur algorithm, which naturally arises in connection with displacement equations, can be used to prove the above-mentioned result. The associated transmission-line interpretation is also discussed in terms of a cascade of elementary sections with intrinsic blocking properties.

16 citations

Proceedings ArticleDOI
27 Sep 2021
TL;DR: In this article, a private multi-server federated learning scheme is proposed, which uses cryptographic and differential privacy concepts to privatize the algorithm over a graph structure, and the authors further show under convexity and Lipschitz conditions, that the privatized process matches the performance of the non-private algorithm.
Abstract: Federated learning involves a central processor that interacts with multiple agents to determine a global model. The process consists of repeatedly exchanging estimates, which may end up divulging some private information from the local agents. This scheme can be inconvenient when dealing with sensitive data, and therefore, there is a need for the privatization of the algorithm. Furthermore, the current architecture of a server connected to multiple clients is highly sensitive to communication failures and computational overload at the server. In this work, we develop a private multi-server federated learning scheme, which we call graph federated learning. We use cryptographic and differential privacy concepts to privatize the federated learning algorithm over a graph structure. We further show under convexity and Lipschitz conditions, that the privatized process matches the performance of the non-private algorithm.

16 citations

Proceedings ArticleDOI
24 Oct 1999
TL;DR: A new (sub-optimal) maximum likelihood estimation algorithm is derived for the time and amplitude of arrival of a known transmitted sequence over a single path fading channel in the case of CDMA wireless location finding.
Abstract: Wireless location finding is receiving increasing attention in the field of wireless communications. This is is due to an order issued by the Federal Communications Commission (FCC) that mandates all wireless service providers to locate an emergency 911 caller within a high accuracy, by the year 2001. We derive a new (sub-optimal) maximum likelihood estimation algorithm for the time and amplitude of arrival of a known transmitted sequence over a single path fading channel. The new algorithm is then applied to the case of CDMA wireless location finding. The paper discusses both simulation and field trial results, all of which demonstrate significant estimation accuracy improvement over known algorithms.

16 citations

Proceedings ArticleDOI
Naofal Al-Dhahir1, Ali H. Sayed1
24 Oct 1999
TL;DR: Close-form expressions for computing the finite-length MIMO MMSE-DFE are presented for two common multi-user detection scenarios and quantifies the diversity performance improvement as a function of the number of transmit/receive antennas and equalizer taps.
Abstract: A new theoretical framework is introduced for analyzing the performance of a finite-length minimum mean square error decision feedback equalizer (MMSE-DFE) in a multi-input multi-output (MIMO) environment. The framework includes transmit and receive diversity systems as special cases and quantifies the diversity performance improvement as a function of the number of transmit/receive antennas and equalizer taps. Closed-form expressions for computing the finite-length MIMO MMSE-DFE are presented for two common multi-user detection scenarios.

16 citations

Proceedings ArticleDOI
27 Apr 1993
TL;DR: A unified square-root-based derivation of adaptive filtering schemes that is based on reformulating the original problem as a state-space linear least-squares estimation problem and suggests some generalizations and extensions of classical results.
Abstract: The authors describe a unified square-root-based derivation of adaptive filtering schemes that is based on reformulating the original problem as a state-space linear least-squares estimation problem. In this process one encounters rich connections with algorithms that have been long established in linear least-squares estimation theory, such as the Kalman filter, the Chandrasekhar filter, and the information forms of the Kalman and Chandrasekhar algorithms. The RLS (recursive least squares), fast RLS, QR, and lattice algorithms readily follow by proper identification with such well-known algorithms. The approach also suggests some generalizations and extensions of classical results. >

16 citations


Cited by
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Journal ArticleDOI

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08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

Journal ArticleDOI
TL;DR: This survey provides an overview of higher-order tensor decompositions, their applications, and available software.
Abstract: This survey provides an overview of higher-order tensor decompositions, their applications, and available software. A tensor is a multidimensional or $N$-way array. Decompositions of higher-order tensors (i.e., $N$-way arrays with $N \geq 3$) have applications in psycho-metrics, chemometrics, signal processing, numerical linear algebra, computer vision, numerical analysis, data mining, neuroscience, graph analysis, and elsewhere. Two particular tensor decompositions can be considered to be higher-order extensions of the matrix singular value decomposition: CANDECOMP/PARAFAC (CP) decomposes a tensor as a sum of rank-one tensors, and the Tucker decomposition is a higher-order form of principal component analysis. There are many other tensor decompositions, including INDSCAL, PARAFAC2, CANDELINC, DEDICOM, and PARATUCK2 as well as nonnegative variants of all of the above. The N-way Toolbox, Tensor Toolbox, and Multilinear Engine are examples of software packages for working with tensors.

9,227 citations

Proceedings ArticleDOI
22 Jan 2006
TL;DR: Some of the major results in random graphs and some of the more challenging open problems are reviewed, including those related to the WWW.
Abstract: We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

7,116 citations

Journal ArticleDOI

6,278 citations

01 Jan 2016
TL;DR: The table of integrals series and products is universally compatible with any devices to read and is available in the book collection an online access to it is set as public so you can get it instantly.
Abstract: Thank you very much for downloading table of integrals series and products. Maybe you have knowledge that, people have look hundreds times for their chosen books like this table of integrals series and products, but end up in harmful downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they cope with some harmful virus inside their laptop. table of integrals series and products is available in our book collection an online access to it is set as public so you can get it instantly. Our book servers saves in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the table of integrals series and products is universally compatible with any devices to read.

4,085 citations