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Showing 1 to 20 of 1113 for “"iteration"”.
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The Sherman Morrison Iteration
The Sherman Morrison iteration method is developed to solve regularized least squares problems. Notions of pivoting and splitting are deliberated on to make the method more robust. The Sherman Morrison iteration method is shown to be effective when dealing with an extremely underdetermined least …
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Iteration procedures for simultaneous equations
Thesis (Sc.D.) Massachusetts Institute of Technology. Dept. of Electrical Engineering, 1954.
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The E² Bathe subspace iteration method
Since its development in 1971, the Bathe subspace iteration method has been widely-used to solve the generalized symmetric-definite eigenvalue problem. The method is particularly useful for solving large eigenvalue problems when only a few of the least dominant eigenpairs are sought. In reference …
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Rates Of Escape Under Iteration Of Analytic Functions
… on sets with a uniform rate of escape under the iteration of transcendental entire functions. We study their properties and their structure as well as using them as a tool to prove some interesting topological results. First, motivated by the work of Rippon and Stallard, we generalise the quite …
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Solving Large MDPs Quickly with Partitioned Value Iteration
Value iteration is not typically considered a viable algorithm for solving large-scale MDPs because it converges too slowly. However, its performance can be dramatically improved by eliminating redundant or useless backups, and by backing up states in the right order. We present several methods …
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Minimax Solution of Statistical Decision Problems by Iteration
Made available in DSpace on 2014-12-10T16:39:48Z (GMT). No. of bitstreams: 1 6604253.pdf: 1644729 bytes, checksum: 80509ed779017c294dbbc563de1c57e7 (MD5) Previous issue date: 1965
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Development and verification of engineering design iteration models
Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 1992.
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Approximate value iteration approaches to constrained dynamic portfolio problems
… solution methods based on approximate value iteration. The primary innovation is the use of mean-variance portfolio selection methods. We present two case studies that employ these approximate value iteration methods. The first case study explores the effect of an insolvency constraint that …
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Convergence of the Arnoldi Iteration for Estimating Extreme Eigenvalues
Krylov subspace methods, like the Arnoldi iteration, are a powerful tool for efficiently solving high-dimensional linear algebra problems. In this work, we analyze the convergence of Krylov methods for estimating the numerical range of a matrix. Prior bounds on approximation error often depend on …
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Phantom work : design iteration timing in new product development
… increases, companies often compress their design iteration cycle times in an effort to develop products more quickly. In many cases, design cycles may overlap creating situations where learning opportunities (e.g. through testing) are missed and/or ignored. More perversely, compressing design …
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Generalized models of design iteration using signal flow graphs
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1995.
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Improvements in the Small Sieve Estimate of Selberg by Iteration
In the notation of H. Halberstam and H.-E. Richert, the small sieve estimate of Selberg is
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Product development cycle time characterization through modeling of process iteration
Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1993.
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On integral equations, their solution by iteration and analytic continuation
Thesis (Ph.D.) Massachusetts Institute of Technology. Dept. of Mathematics, 1950.
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Multi-Objective Optimization: Riccati Iteration and the Lotfi Manufacturing Problem
… powerful solution technique known as the Riccati Iteration is such a novel approach, and can be applied to complex problems that would otherwise be infeasible to solve. This thesis will demonstrate the power of the Riccati iteration by employing the Riccati iteration with spreadsheet software to …
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Improved worst-case regret bounds for randomized least-squares value iteration
… algorithm, randomized least-squares value iteration (RLSVI). Our $\tilde{\mathrm{O}}(H^2S\sqrt{AT})$ high-probability worst-case regret bound improves the previous sharpest worst-case regret bounds for RLSVI and matches the existing state-of-the-art worst-case TS-based regret bounds.
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A unified iteration space transformation framework for sparse and dense tensor algebra
… can be applied to irregular loops over sparse iteration spaces. I also show how these transformations can be applied to the contiguous value arrays of sparse tensor data structures, which I call their position spaces, to unlock load-balanced tiling and parallelism. These concepts have been …
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[I³] imitation, iteration and improvisation : embodied interaction in computational making and learning
… F for its three-layer operation of Imitation, Iteration and Improvisation. Drawing upon research from other fields, this methodology for human-machine making and learning is based on a recursive process of embodied, situated interaction between learners, machines, materials, and the …
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The programming of Laplace's equation for solution by iteration on Whirlwind I
Thesis (B.S.) Massachusetts Institute of Technology. Dept. of Physics, 1950.
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