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Filtering by: Creator Fridley, Daniel Seth Remove constraint Creator: Fridley, Daniel Seth Degree Field Computer Science Remove constraint Degree Field: Computer Science Degree Level Doctoral Remove constraint Degree Level: Doctoral

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  • Information Theoretical Analysis of Self-Similar Trees

    Creator:
    Chunikhina, Evgenia V.
    Abstract:
    Tree-like patterns are ubiquitous in nature. Botanical trees, river networks, and blood systems are the most well-known examples of complex hierarchical systems met in observations. Interestingly, many of such systems exhibit statistical self-similarity. There are two main types of self-similarity: Horton self-similarity and Tokunaga self-similarity. Although there is an increased...
    Resource Type:
    Dissertation

  • A linear equation model for a family of interconnection networks

    Creator:
    Larson, Shawn M.
    Abstract:
    The most important part of parallel computation is communication. Except in the most embarassingly parallel examples, processors cannot work cooperatively to solve a problem unless they can communicate. One way to solve the problem of communication is to use an interconnection network. Processors are located at nodes of the network,...
    Resource Type:
    Dissertation

  • Optimizing Cryptographic Obfuscation

    Creator:
    Carmer, Brent
    Abstract:
    Cryptographic obfuscation is a powerful tool that makes programs “unintelligible” yet still runnable. It essentially gives programs the ability to keep secrets. The practical applications of obfuscation range from keeping secrets in banking applications to preventing software theft to providing secure messaging applications. The cryptographic applications of obfuscation are also...
    Resource Type:
    Dissertation
    Full Text:
    was accepted to the 2016 ACM CCS conference and has co-authors Kevin Lewi, Alex J. Malozemoff, Daniel

  • Communication efficient private set and database operations

    Creator:
    Garimella, Gayathri Annapurna
    Abstract:
    Secure Computation is a powerful tool that enables a set of parties to jointly compute any function over their private inputs, without a trusted third party. Private Set Intersection is a specific case of two-party Secure Computation, where Alice (with private set X) and Bob (with private set Y) specifically...
    Resource Type:
    Dissertation

  • Keeping your Friends Secret: Improving the Security, Effciency and Usability of Private Set Intersection

    Creator:
    Rindal, Peter B.
    Abstract:
    Private set intersection (PSI) allows two parties, who each hold a set of items, to compute the intersection of those sets without revealing anything about other items. Recent advances in PSI have significantly improved its performance for the case of semi-honest security, making semi-honest PSI a practical alternative to insecure...
    Resource Type:
    Dissertation
    Full Text:
    field of Cryptography. • My coauthors which include Hao Chen, Daniel Demmler, Kim Laine, Kristin

  • Efficient Private Matching for Private Databases

    Creator:
    Trieu, Thi Ni Ni
    Abstract:
    Private matching (PM) is a key cryptographic primitive in secure computation that allows several parties to jointly compute some functions depending on their private inputs. Indeed, this primitive has many practical applications. For instance, in online advertising, two companies may wish to find their common customers for a joint marketing...
    Resource Type:
    Dissertation
    Full Text:
    , Daniel Demm- ler, Vladimir Kolesnikov, Ranjit Kumaresan, Naor Matania, Benny Pinkas, Peter Rindal

  • Topological analysis, visualization, and design of vector fields on surfaces

    Creator:
    Chen, Guoning
    Abstract:
    Analysis, visualization, and design of vector fields on surfaces have a wide variety of major applications in both scientific visualization and computer graphics. On the one hand, analysis and visualization of vector fields provide critical insights to the flow data produced from simulation or experiments of various engineering processes. On...
    Resource Type:
    Dissertation

  • Learning with Partial Supervision for Clustering and Classification

    Creator:
    Pei, Yuanli
    Abstract:
    In the field of machine learning, clustering and classification are two fundamental tasks. Traditionally, clustering is an unsupervised method, where no supervision about the data is available for learning; classification is a supervised task, where fully-labeled data are collected for training a classifier. In some scenarios, however, we may not...
    Resource Type:
    Dissertation

  • Machine Learning for Precision Medicine: Application to Cancer Chemotherapy Response Prediction and Wound Healing Status Assessment

    Creator:
    Wei, Qi
    Abstract:
    Ph.D. candidate Qi Wei's thesis consists of two projects: Chemotherapy Project: a study based on the research paper "Predicting chemotherapy response of various cancer types using a variational auto-encoder approach" submitted to the bioRxiv preprint archive and accepted by the BMC bioinformatics; and Wound Monitor Project: implementing and assessing analytics...
    Resource Type:
    Dissertation