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Filtering by: Creator Fox, David S. Remove constraint Creator: Fox, David S. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science Subject Computer algorithms Remove constraint Subject: Computer algorithms

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  • Fast algorithms and applications for multi-dimensional least-squares-based minimum variance spectral estimation

    Creator:
    Wei, Lin
    Abstract:
    The main contributions of this thesis are the development and application of four computationally efficient solutions for least-squares-based (LS-based) minimum variance spectral estimation (MVSE). They are: (1) fast computational solution for the 1-D covariance LS-based MVSE, (2) fast computational solution for the 1-D modified covariance LS-based MVSE, (3) fast computational...
    Resource Type:
    Dissertation
    Full Text:
    Advisor: Dr. S. Lawrence Marple, Jr. AN ABSTRACT OF THE THESIS OF Lin Wei for the degree of Doctor

  • Algorithms for massive biological datasets

    Creator:
    Bryant, Douglas W. (Douglas Wesley)
    Abstract:
    Within the past several years the technology of high-throughput sequencing has transformed the study of biology by offering unprecedented access to life's fundamental building block, DNA. With this transformation's potential a host of brand-new challenges have emerged, many of which lend themselves to being solved through computational methods. From de...
    Resource Type:
    Dissertation
    Full Text:
    S. suis, 43.8% of the 36mer Illumina reads in the data set matched perfectly to the reference genome

  • Incorporating labeled features into image classification using generalized expectation

    Creator:
    Moore, Travis
    Abstract:
    Image classification is a difficult problem, often requiring large training sets to get satisfactory results. However this is a task that humans perform very well, and incorporating user feedback into these learning algorithms could help reduce the dependency on large amounts of labeled training data. This process has already been...
    Resource Type:
    Masters Thesis
    Full Text:
    , if a segment has a SIFT vector s, and it is clustered into group j, then we say that the feature

  • Structured gradient boosting

    Creator:
    Parker, Charles (Charles Lincoln)
    Abstract:
    The goal of many machine learning problems can be formalized as the creation of a function that can properly classify an input vector, given a set of examples of that function. While this formalism has produced a number of success stories, there are notable situations in which it fails. One...
    Resource Type:
    Dissertation

  • Predicting activity type from accelerometer data

    Creator:
    Zheng, Yonglei
    Abstract:
    The study of physical activity is important in improving people’s health as it can help people understand the relationship between physical activity and health. Accelerometers, due to its small size, low cost, convenience and its ability to provide objective information about the frequency, intensity, and duration of physical activity, has...
    Resource Type:
    Masters Thesis
    Full Text:
    i=1 si. O(N) [5, 6, 19, 28, 29] 3. Standard deviation: σs = √ 1 N ∑N i=1(si − us). O(N) [5, 6

  • Timing Attacks on Software Implementation of RSA

    Creator:
    Singh, Harshman
    Abstract:
    Timing attacks enable an attacker to extract secret information from a cryptosystem by observing timing differences with respect to different inputs given to an encryption or decryption algorithm. Werner Schindler has proposed a timing attack on smart card devices. We implemented this attack based on the same approach for RSA...
    Resource Type:
    Capstone Project
    Full Text:
    answered my questions and provided me with lot of inputs. Special thanks to David Brumley for clarifying

  • A probabilistic framework and algorithms for modeling and analyzing multi-instance data

    Creator:
    Behmardi, Behrouz
    Abstract:
    Multi-instance data, in which each object (e.g., a document) is a collection of instances (e.g., word), are widespread in machine learning, signal processing, computer vision, bioinformatic, music, and social sciences. Existing probabilistic models, e.g., latent Dirichlet allocation (LDA), probabilistic latent semantic indexing (pLSI), and discrete component analysis (DCA), have been...
    Resource Type:
    Dissertation
    Full Text:
    feature transformation defined over X . In 9 principle, many p.d.f.’s can satisfies the constraints

  • Multi-instance multi-label learning : algorithms and applications to bird bioacoustics

    Creator:
    Briggs, Forrest
    Abstract:
    We consider the problem of supervised classification of bird species from audio recordings in a real-world acoustic monitoring scenario (i.e. audio data is collected in the field with an omnidirectional microphone, without human supervision). Obtaining better data about bird activity can assist conservation efforts, and improve our understanding of their...
    Resource Type:
    Dissertation