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Filtering by: Creator Bira, Nicholas P. Remove constraint Creator: Bira, Nicholas P. Degree Field Computer Science Remove constraint Degree Field: Computer Science

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  • Learning functional descriptions from examples

    Creator:
    Flann, Nicholas S.
    Abstract:
    The task of inductive learning from examples places constraints on the representation of training instances and concepts. These constraints are different from, and often incompatible with, the constraints placed on the representation by the performance task. This incompatibility is severe when learning functional concepts and explains why previous researchers have...
    Resource Type:
    Masters Thesis
    Full Text:
    ABSTRACT OF THE THESIS OF Nicholas S. Flann for the degree of Master of Science in Computer Science pre

  • Correct abstraction in counter-planning : a knowledge compilation approach

    Creator:
    Flann, Nicholas S.
    Abstract:
    Knowledge compilation improves search-intensive problem-solvers that are easily specified but inefficient. One promising approach improves efficiency by constructing a database of problem-instance/best-action pairs that replace problem-solving search with efficient lookup. The database is constructed by reverse enumeration- expanding the complete search space backwards, from the terminal problem instances. This approach...
    Resource Type:
    Dissertation
    Full Text:
    compilation approach AN ABSTRACT OF THE THESIS OF Nicholas S. Flann for the degree of Doctor of Philosophy

  • Supporting merge comprehension when resolving merge conflicts

    Creator:
    Nelson, Nicholas
    Abstract:
    Distributed version control allows developers to manage software evolution among distributed development teams. But it does not eliminate all consistency and concurrency issues, and instead introduces additional complexity when merging code. And resolving merge conflicts is nontrivial when automated merging fails. In such cases, developers are forced to inspect the...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Nicholas Nelson for

  • 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
    Full Text:
    Media Sensors for Twitter Abstract approved: Scott P. Sanner Social media sources such as Twitter

  • Species Distribution Modeling of Citizen Science Data as A Classification Problem with Class-Conditional Label Noise

    Creator:
    He, Liqiang
    Abstract:
    Species distribution models (SDM), which quantify the correlation between the distribution of a species and environmental factors, are increasingly used to map and monitor animal and plant distributions in the context of awareness of environmental change and its ecological consequence. For perfect data, this is a straightforward classification problem from...
    Resource Type:
    Masters Thesis
    Full Text:
    thank my thesis committee: Prof. Thomas G. Dietterish, Prof. Amir Nayyeri and Prof. John P. Bolte, for

  • Graph Imitation Learning for Optimal Joint Beamforming and Antenna Selection

    Creator:
    Shrestha, Sagar
    Abstract:
    Transmit beamforming is an important technique employed to improve efficiency and signal quality in wireless communication systems by steering signals towards their in- tended users. It often arises jointly with the antenna selection problem due to various reasons, such as limited number of radio frequency (RF) chains and energy/resource effi-...
    Resource Type:
    Masters Thesis
    Full Text:
    corresponds to a branching (partitioning a node) operation. Use P(t) to denote the collection of (s, ℓ

  • Poisoning machine learning models to increase membership inference risks

    Creator:
    Le, Hoang
    Abstract:
    Deep learning is now being utilized widely in applications where sensitive data is being used for model training, for example, in health care. In this scenario, any data leakage will cause privacy concerns to whose data records are used to train the model. An attacker can actively cause privacy leakage...
    Resource Type:
    Masters Thesis
    Full Text:
    , and Dr. Matthew Jagielski and Dr. Nicholas Carlini from Google. My work, under the guidance of Dr

  • Facilitating Code Comprehension by Annotations in Canvas-Based IDE

    Creator:
    Adeli, Marjan
    Abstract:
    Developers spend a considerable amount of time comprehending code and building accurate mental models of the code. Understanding the relationships between software features within IDEs is difficult, with information split across different visual hierarchies making navigation cumbersome. Canvas-based IDEs mitigate some of the navigation costs by allowing relevant information to...
    Resource Type:
    Masters Thesis
    Full Text:
    Souti Chattopadhyay and Nicholas Matthew Nelson. I also express my gratitude to my family and friends

  • A fast algorithm for determining the primitivity of an n x n nonnegative matrix

    Creator:
    Leegard, Amanda D.
    Abstract:
    Nonnegative matrices have a myriad of applications in the biological, social, and physical genres. Of particular importance are the primitive matrices. A nonnegative matrix, M, is primitive exactly when there is a positive integer, k, such that M[superscript k] has only positive entries; that is, all the entries in M[superscript...
    Resource Type:
    Masters Thesis
    Full Text:
    .................................................................. 11 LIST OF EQUATIONS EQuation Page 2.1 P[i} = number of edges needed to be followed to reach

  • 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:
    Table Page 6.1 Benchmark Acceptance Rate by Metric and p-value . . . . . . . . . 46 6.2 Benchmark