Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 37 for “"coordinate descent"”.
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Efficient coordinate descent for ranking with domination loss
We define a new batch coordinate-descent ranking algorithm based on a domination loss, which is designed to rank a small number of positive examples above all negatives, with a large penalty on false positives. Its objective is to learn a linear ranking function for a query with labeled training …
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Computationally Efficient Multiuser and MIMO Detection based on Dichotomous Coordinate Descent Iterations
… These detectors are based on Dichotomous Coordinate Descent (DCD) iterations, which are multiplication and division free, and therefore are attractive for real-time implementation. We propose a box-constrained DCD algorithm, and apply it to multiuser detection. We also design an FPGA …
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Interval method for special constrained global optimization problems
… Three different procedures are developed (coordinate descent method, cutting line method, and projection coordinate descent method) to locate a feasible sampling point for the two linear constraints. Numerical results are illustrated to show the effectiveness in Chapter 5. The three …
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Algorithms for matrix completion
… We introduce a scalable primal-dual block coordinate descent algorithm for large sparse matrix completion. The algorithm explicitly maintains a sparse dual and the corresponding low rank primal solution at the same time. Preliminary empirical results illustrate both the scalability and the …
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Performance Analysis of the Apple AMX Matrix Accelerator
… dependency) terms. Fitted with non-negative coordinate descent on length-2 loops and validated on length-3 sequences via a lightweight loop simulation, the model obtains reasonably high accuracy while remaining helpful for those trying to understand the architecture.
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Differential Dependency Network and Data Integration for Detecting Network Rewiring and Biomarkers
… Secondly, the computational time of the block coordinate descent algorithm in DDN increases rapidly with the number of involved samples and molecular entities. To address the imbalanced sample group problem, we propose a sample-scale-wide normalized formulation to correct systematic bias and …
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Temporally Feathered Radiation Therapy under Uncertainty
… To solve the resulting models, we design block coordinate descent algorithms and demonstrate their performance across applications in stochastic TFRT, portfolio management, and capacity expansion.
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High-Dimensional Covariate-Dependent Gaussian Graphical Models
… using penalized composite likelihood, employing coordinate descent and Broyden’s method for optimization under different scenarios. We provide theoretical results ensuring both parameter and sign consistency of the proposed estimator. The method is applied to the same influenza vaccine dataset, …
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Large-Scale Optimization Methods: Theory and Applications
… In this thesis, we show the efficiency of coordinate descent (CD) and mirror descent (MD) methods in solving large-scale optimization problems. First, we investigate the convergence rate of the CD method with different coordinate selection rules. We present certain problem classes, for …
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Variable screening and graphical modeling for ultra-high dimensional longitudinal data
… graph for longitudinal data. We used pairwise coordinate descent combined with second order cone programming to optimize the penalized likelihood and estimate the parameters. Furthermore, we extended the nodewise regression method the for longitudinal data case. Simulation and real data …
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Convex relaxation methods for graphical models : Lagrangian and maximum entropy approaches
… minimizes the Lagrangian dual function by block coordinate descent. This results in an iterative marginal-matching procedure that enforces consistency among the subgraphs using an adaptation of the well-known iterative scaling algorithm. This approach is developed both for discrete variable and …
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Some Advanced Model Selection Topics for Nonparametric/Semiparametric Models with High-Dimensional Data
… function of the similarity matrix. An efficient coordinate descent/backfitting algorithm is developed. The third topic involves a specific genetic pathway dataset in which the pathways interact with the environmental variables. We propose a semiparametric method to model the pathway-environment …
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Statistical Methods for Complex and/or High Dimensional Data
… of convex programming, augmented Lagrange and coordinate descent methods. Furthermore, we show that the aforementioned nnFSG method recovers the oracle estimate consistently, and yields a bound on the mean squared errors (MSE).} Besides, we examine the performance of our method by using finite …
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Critical Evaluation of DC-Grid and Strong Grid-Forming Wind Generator Systems
… optimization methodology combining the coordinate descent method and NSGA-II algorithms successfully reduces the synchronous reactance from 2.82 per unit (pu) to 0.94 pu for a 5-MW T-WRSG, enabling effective operation with passive diode rectifiers. Experimental validation using a 4.2-kW …
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Analyzing intentions from big data traces of human activities
… we design an accelerated stochastic block coordinate descent method with optimal sampling; for optimizing non-strongly convex objectives, we design a stochastic variance reduced alternating direction method of multipliers with the doubling-trick. Inevitably, human activities are …
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Challenges in recommender systems : scalability, privacy, and structured recommendations
… primal solution. We provide a new dual block coordinate descent algorithm for solving the dual problem with a few spectral constraints. Empirical results illustrate the effectiveness of our method in comparison to recently proposed alternatives. In addition, we extend the method to …
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Successive convex approximation: analysis and applications
The block coordinate descent (BCD) method is widely used for minimizing a continuous function f of several block variables. At each iteration of this method, a single block of variables is optimized, while the remaining variables are held fixed. To ensure the convergence of the BCD method, the …
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Algorithms for Large-scale Data Analytics and Applications to the COVID-19 Pandemic
… and developed a projected stochastic gradient descent method, fastImpute, to solve matrix completion 20x faster than state-of-the-art methods while providing optimality guarantees. In Chapter 2, we introduce the Interpretable Matrix Completion problem (IMC) to provide meaningful insights for …
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Methods for convex optimization and statistical learning
… methods -- namely Frank-Wolfe and greedy coordinate descent -- as instantiations of the dual averaging method of Nesterov, and we discuss the implications thereof. In the third part of the thesis, we present an extension of the Frank-Wolfe method that is designed to induce near-optimal …
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Model-based methods for high-dimensional multivariate analysis
… To compute our estimators, we use a blockwise coordinate descent algorithm. To update the optimization variables corresponding to response category mean matrices, we use an alternating minimization algorithm that takes advantage of the Kronecker structure of the precision matrix. We show that …
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