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Full-Text Articles in Physical Sciences and Mathematics
Neural Machine Translation, Quinn M. Lanners, Thomas Laurent
Neural Machine Translation, Quinn M. Lanners, Thomas Laurent
Honors Thesis
Neural Machine Translation is the primary algorithm used in industry to perform machine translation. This state-of-the-art algorithm is an application of deep learning in which massive datasets of translated sentences are used to train a model capable of translating between any two languages. The architecture behind neural machine translation is composed of two recurrent neural networks used together in tandem to create an Encoder Decoder structure. Attention mechanisms have recently been developed to further increase the accuracy of these models. In this senior thesis, the various parts of Neural Machine Translation are explored towards the eventual creation of a tutorial …
Credit Risk Analysis Using Machine Learning And Neural Networks, Dhruv Dhanesh Thanawala
Credit Risk Analysis Using Machine Learning And Neural Networks, Dhruv Dhanesh Thanawala
Dissertations, Master's Theses and Master's Reports
A key activity within the banking industry is to extend credit to customers, hence,
credit risk analysis is critical for nancial risk management. There are various methods
used to perform credit risk analysis. In this project, we analyze German and
Australian nancial data from UC Irvine Machine Learning repository, reproducing
results previously published in literature. Further, using the same dataset and various
machine learning algorithms, we attempt to create better models by tuning available
parameters, however, our results are at best comparable to published results.
In this report, we have explained the algorithms and mathematical framework that
goes behind developing …
Randomized Algorithms For Preconditioner Selection With Applications To Kernel Regression, Conner Dipaolo
Randomized Algorithms For Preconditioner Selection With Applications To Kernel Regression, Conner Dipaolo
HMC Senior Theses
The task of choosing a preconditioner M to use when solving a linear system Ax=b with iterative methods is often tedious and most methods remain ad-hoc. This thesis presents a randomized algorithm to make this chore less painful through use of randomized algorithms for estimating traces. In particular, we show that the preconditioner stability || I - M-1A ||F, known to forecast preconditioner quality, can be computed in the time it takes to run a constant number of iterations of conjugate gradients through use of sketching methods. This is in spite of folklore which …
Efficient Local Comparison Of Images Using Krawtchouk Descriptors, Julian Deville
Efficient Local Comparison Of Images Using Krawtchouk Descriptors, Julian Deville
Online Theses and Dissertations
It is known that image comparison can prove cumbersome in both computational complexity and runtime, due to factors such as the rotation, scaling, and translation of the object in question. Due to the locality of Krawtchouk polynomials, relatively few descriptors are necessary to describe a given image, and this can be achieved with minimal memory usage. Using this method, not only can images be described efficiently as a whole, but specific regions of images can be described as well without cropping. Due to this property, queries can be found within a single large image, or collection of large images, which …