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Least squares and the not-Normal Equations
Published 2025“…For many of the classic problems of linear algebra, effective and efficient numerical algorithms exist, particularly for situations where dimensions are not too large. <br> The linear least squares problem is one such: excellent algorithms exist when QR factorisation is feasible. …”
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Distributed Singular Value Decomposition Through Least Squares
Published 2024“…We show the efficacy of a distributed stochastic gradient descent algorithm by implementing parallelized alternating least squares and prove theoretical guarantees for its convergence and empirical results, which allow for the development of a simple framework for solving SVD in a correct, scalable, and easily optimizable manner.…”
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FAST: An Optimization Framework for Fast Additive Segmentation in Transparent ML
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Orthogonal vs. uncorrelated least squares discriminant analysis for feature extraction
Published 2013“…We show that the orthogonal least squares discriminant analysis is an extension to the null space linear discriminant analysis, and the uncorrelated least squares discriminant analysis is exactly equivalent to the traditional linear discriminant analysis. …”
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Journal Article -
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Production sequence generation and tolerance allocation for least production cost optimization
Published 2009“…This thesis presents an approach that is capable of determining the optimal production sequence and its optimal process tolerances to achieve the least production costs.…”
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Thesis -
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A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) /
Published [202Subjects: “…Least squares…”
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An incremental trust-region method for Robust online sparse least-squares estimation
Published 2013“…In this paper we present Robust Incremental least-Squares Estimation (RISE), an incrementalized version of the Powell's Dog-Leg trust-region method suitable for use in online sparse least-squares minimization. …”
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Mitigating quantization effects on distributed sensor fusion : a least squares approach
Published 2020“…To tackle this challenging issue, we introduce the notion of virtual measurements and propose a distributed solution LS-DSFS, which is a combination of a quantized consensus algorithm and the least squares approach. We provide detailed analysis of the LS-DSFS on its performance in terms of unbiasedness and mean square property. …”
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Journal Article -
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At-least-potentially-non-contrastive transcendence in Tanner’s God and Creation in Christian Theology
Published 2025Journal article -
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Optimizing hybrid energy systems for remote communities in Asia’s least developed countries
Published 2024“…In least-developed countries (LDCs), electricity shortages are the primary barrier to economic and social growth. …”
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Characterization of nickel-titanium based thin films crystallized by fast and ultra-fast annealing methods
Published 2012“…The fast crystallization process allows the precise control of microstructure in a lower thermal budget (product of processing temperature and time). …”
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Thesis -
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One-Pass Learning via Bridging Orthogonal Gradient Descent and Recursive Least-Squares
Published 2025“…By doing so, we bridge two seemingly distinct algorithms in adaptive filtering and machine learning, namely the recursive least-squares (RLS) algorithm and orthogonal gradient descent (OGD). …”
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Fast prototyping of neural network application
Published 2022“…To solve the problem of fast training and classification, hardware accelerator is proposed. …”
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Thesis-Master by Coursework -
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Fast numerical methods for image restoration
Published 2012“…The other one is graph cuts technique for fast solving higher order curvature based models. …”
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Thesis -
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Marketing strategies of fast food chains
Published 2015“…The motivating force that spearheaded us to take on this project ts the inherent competitiveness of the fast food industry. We are more curious, rather than fascinated, by how the restaurants remain competitive despite the tense competition in the market. …”
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Final Year Project (FYP) -
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