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 18 of 18 for “"Boosting Algorithm"”.
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An efficient boosting algorithm for combining preferences
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.
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A Direct Algorithm for the K-Nearest-Neighbor Classifier via Local Warping of the Distance Metric
… is the large model size. There are a number of algorithms that are able to condense the model size of the k-NN classifier at the expense of accuracy. Boosting is therefore desirable for increasing the accuracy of these condensed models. Unfortunately, there does not exist a boosting algorithm …
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AI-infused security: Robust defense by bridging theory and practice
… the deep connection between game theory and boosting, we develop a communication-efficient distributed boosting algorithm with strong theoretical guarantees in the agnostic learning setting. (3) Using AI to Protect Enterprise and Society: We show how AI can be used in real enterprise …
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Robust methods in data mining
… - in particular, classification trees and boosting. The boosting algorithm is a relative newcomer to the classification portfolio that seeks to enhance the performance of classifiers by iteratively re-weighting the data according to their previous classification status. We explore the …
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Methods for convex optimization and statistical learning
… sequence, (ii) a novel adjustment to the basic algorithm to better account for warm-start information, and (iii) extensions of the computational guarantees that hold in the presence of approximate subproblem and/or gradient computations. In the second part of the thesis, we present a unifying …
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Automatic real-time facial expression recognition for signed language translation
… units based on Haar features and the Adaboost boosting algorithm. This method achieves equally high recognition accuracy for certain AUs but operates two orders of magnitude more quickly than the Gabor+SVM approach. Finally, we developed a software prototype of a real-time, automatic signed …
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A Deep Learning Based Pipeline for Image Grading of Diabetic Retinopathy
… retina image processing, deep learning, and a boosting algorithm for high-performance DR grading. First, we preprocess the retina image datasets to highlight signs of DR, then follow by a convolutional neural network to extract features of retina images, and finally apply a boosting tree …
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Multiple classifier combination through ensembles and data generation
… namely the DataBoost and DataBoost-IM algorithms, to extend Boosting algorithms' predictive performance. The DataBoost algorithm is designed to assist Boosting algorithms to avoid over-emphasizing hard examples. In the DataBoost algorithm, new synthetic data with bias information …
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Tree-based Methods for Learning Probability Distributions
… explored with a new sequential Monte Carlo algorithm. The new ensemble method discussed in Chapter 3 is proposed under a new addition rule defined for probability distributions. The new rule based on cumulative distribution functions and their generalizations enables us to smoothly introduce …
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Robust learning and segmentation for secure understanding
… are by no means limited to this application. Boosting techniques are popular because they learn effective classification functions and identify the most relevant features at the same time. However, in general, they overfit and perform poorly on data sets that contain many features, but few …
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Short-term traffic forecasting for a smart satellite communications system
… of single user models using a gradient boosting algorithm, and a multi-user model using Long- Short Term Memory neural networks (LSTM) or Gated Recurrent Unit neural networks (GRU) to forecast terminal traffic. Each algorithm was tuned using a two-stage design of experiments process …
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An Experimental and Numerical Study on Metakaolin-based Geopolymers
… were tested, among which the extreme gradient boosting algorithm was able to classify the GPs with 80% accuracy in three levels of ‘low’, ‘medium’, and ‘high’ strength and predict the strength with R2 = 0.80 given the composition and test age. In the second part, a seeding method was used to …
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A systematic study of offline recognition of Thai printed and handwritten characters
… the three datasets (7.6 percentage points). A boosting algorithm called AdaBoost yields a slight improvement in recognition rate (1.2 percentage points) over the original classifiers (without applying the AdaBoost algorithm).
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From data to decision : boosting for time-constrained detection of objects in moving video
… cascade of classifiers trained using the popular boosting algorithm, RealBoost, is adopted as the baseline system for our research, with novel improvements building upon this framework. The approach attempts to follow the full throughput of such systems, starting from the input training data, …
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From data to decision : boosting for time-constrained detection of objects in moving video
… cascade of classifiers trained using the popular boosting algorithm, RealBoost, is adopted as the baseline system for our research, with novel improvements building upon this framework. The approach attempts to follow the full throughput of such systems, starting from the input training data, …
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Canaries in the coal mine: Boosted machine learning for the classification of recessions in the eurozone business cycle
… analysis, XGBoost was used to provide a gradient boosting framework. Using quarterly GDP values for all of the EA19 (with the exception of Ireland due to data availability), business cycle data was produced using the Bry-Boschan algorithm, coupled with seasonal and calendar smoothing via Eurostat. …
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Designing, Modeling, and Optimizing Transactional Data Structures
… TM frameworks, and by presenting two novel STM algorithms in order to enhance the overall performance of those frameworks. Finally, we address the modeling challenge by presenting two models for concurrent and transactional data structures designs. • Our first main contribution in this …
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Artificial Intelligence for Predictive Design and Development of Innovative Materials, Manufacturing Processes, and Technological Applications
L'abstract è presente nell'allegato / the abstract is in the attachment