Search Constraints

Start Over
Filtering by: Creator Samuelsen, Andrew Ira Remove constraint Creator: Samuelsen, Andrew Ira Degree Field Computer Science Remove constraint Degree Field: Computer Science

Search Results

  • A Benchmarking Study of Unsupervised Anomaly Detection Algorithms

    Creator:
    Emmott, Andrew F.
    Abstract:
    It is common practice in the unsupervised anomaly detection literature to create experimental benchmarks by sampling from existing supervised learning datasets. We seek to improve this practice by identifying four dimensions important to real-world anomaly detection applications --- point difficulty, clusteredness of anomalies, relevance of features, and relative frequency of...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE THESIS OF Andrew Emmott for the

  • High-performance data-parallel input/output

    Creator:
    Moore, Jason Andrew
    Abstract:
    Existing parallel file systems are proving inadequate in two important arenas: programmability and performance. Both of these inadequacies can largely be traced to the fact that nearly all parallel file systems evolved from Unix and rely on a Unix-oriented, single-stream, block-at-a-time approach to file I/O. This one-size-fits-all approach to parallel...
    Resource Type:
    Dissertation

  • Learning Topical Social Media Sensors for Twitter

    Creator:
    Iman, Zahra
    Abstract:
    Social media sources such as Twitter represent a massively distributed social sensor over diverse topics ranging from social and political events to entertainment and sports news. However, due to the overwhelming volume of content, it can be difficult to identify novel and significant content within a broad topic in a...
    Resource Type:
    Masters Thesis

  • Image Based Crypto

    Creator:
    Basa, Gungor
    Abstract:
    The ability to create reproducible cryptographically secure keys from temporal environments (e.g., images) has the potential to be a contributor to effective cryptographic mechanisms. Due to the noisy nature of these environments, achieving this goal in a user friendly fashion is a very challenging task, especially since there exists a...
    Resource Type:
    Masters Thesis

  • Assessing and Finding Faults in AI: Two Empirical Studies

    Creator:
    Khanna, Roli
    Abstract:
    With the advent of Artificial Intelligence (AI) in every sphere of life in today's day and age, it has become increasingly important for non-AI experts to be able to comprehend the underlying logic of how AI systems work, assess them and find faults in these systems, particularly when they are...
    Resource Type:
    Masters Thesis
    Full Text:
    , Andrew Anderson, Rupika Dikkala, Jed Irvine, Zeyad Shureih, Kin-Ho Lam, Caleb R. Matthews, Minsuk Kahng

  • Explanations and Processes to Enable Humans to Assess AI with Respect to Manipulable Properties

    Creator:
    Dodge, Jonathan E.
    Abstract:
    Assessing AI systems is difficult. Humans rely on AI systems in increasing ways, both visible and invisible, meaning a variety of stakeholders need a variety of assessment tools (e.g., a professional auditor, a developer, and an end user all have different needs). We posit that it is possible to provide...
    Resource Type:
    Dissertation
    Full Text:
    taught me that learning is a great pastime; Andrew Anderson, my colleague in PhD trials and tribulations

  • 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

  • A tutorial interface for a problem-solving production system

    Creator:
    Lantz, Brian Scott
    Abstract:
    The system described is an interface between a student and a problem-solving production system that solves some class of problems. Its purpose is to help a student learn some part of the realm of problem solving. As a student attempts to solve a problem the system controls the firing of...
    Resource Type:
    Masters Thesis