Search Constraints

Start Over
Filtering by: Alternative title ssim 4-H 320-36 Remove constraint Alternative title ssim: 4-H 320-36 Committee Member Fern, Alan Remove constraint Committee Member: Fern, Alan Language English [eng] Remove constraint Language: English [eng]

Search Results

  • Anomaly Detection and Probabilistic Diagnosis for Automated Data Quality Control

    Creator:
    Zemicheal, Tadesse H.
    Abstract:
    Advances in sensor technology are greatly expanding the range of quantities that can be measured while simultaneously reducing the cost. However, deployed sensors drift out of calibration and fail, so every sensor network requires quality control procedures to promptly detect these failures. To address these problems, we propose a two-level...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Tadesse H. Zemicheal

  • 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:
    would like to thank my entire committee, Weng-Keen Wong, Stewart Trost, Alan Fern and Kenneth H. Funk

  • Statistical Properties and Guarantees for Certain Anomaly Detection Relevant Problems

    Creator:
    Liu, Si
    Abstract:
    Anomaly detection aims at detecting the points that appear different than the majority of the data, such that they are suspected to be generated from a different distribution. Anomaly detectors have been applied in many different fields, such as detecting fraudulent behaviors in bank transaction, finding broken sensors in a...
    Resource Type:
    Dissertation
    Full Text:
    Zemicheal. Risheek Garrepalli, Dr. Alan Fern and Dan Hendrycks contributed to Chapter 4. Tadesse Zemicheal

  • Agile Bipedal Locomotion via Hierarchical Control by Incorporating Physical Principles, Learning, and Optimization

    Creator:
    Green, Kevin
    Abstract:
    Robotic Bipedal locomotion holds the potential for efficient, robust traversal of difficult terrain. The difficulty lies in the dynamics of locomotion which complicate control and motion planning. Bipedal locomotion dynamics are dimensionally large problems, extremely nonlinear, and operate on the limits of actuator capabilities, which limit the performance of generic...
    Resource Type:
    Dissertation
    Full Text:
    Laws . . . . . . . . . . . . . . . . . . . . . . 4 1.2.2 Virtual Model Control

  • Object detection in biological images using a search-based framework

    Creator:
    Lam, Michael
    Abstract:
    This thesis addresses a basic problem in computer vision, that of semantic labeling of images. Our work is aimed at object detection in biological images for evolutionary biology research. In particular, our goal is to detect nematocysts in Scanning Electron Microscope (SEM) images. This biological domain presents challenges for existing...
    Resource Type:
    Masters Thesis
    Full Text:
    is to uncover high-quality outputs, guided by the heuristic function H. Prior work [4, 5] has shown

  • Characterizing and Addressing Dataset Shift with Deep Learning

    Creator:
    Olson, Matthew L.
    Abstract:
    This dissertation delves into understanding, characterizing, and addressing dataset shift in deep learning, a pervasive issue for deployed machine learning systems. Integral aspects of the problem are examined: We start with the use of counterfactual explanations in order to characterize the behavior of deep reinforcement learning agents in visual input...
    Resource Type:
    Dissertation
    Full Text:
    Covariate Shift with Intelligent User Interfaces . . . . . . . . 4 1.3 Unsupervised Cross-Dataset Attribute

  • Scaling multiagent reinforcement learning

    Creator:
    Proper, Scott
    Abstract:
    Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity or "outcome space" explosion. Multiagent domains are particularly susceptible to these problems. This thesis describes ways to mitigate these curses in several different multiagent domains, including real-time delivery of products...
    Resource Type:
    Dissertation
    Full Text:
    CONTENTS (Continued) Page 4 Multiagent Learning 51 4.1 Multiagent H-learning

  • Navigation and coordination of autonomous mobile robots with limited resources

    Creator:
    Knudson, Matthew D.
    Abstract:
    The use of autonomous robots in complex exploration tasks is rapidly increasing. Indeed, robots can provide speed and cost effectiveness in many tasks, as well as allow operation in environments that are hostile to humans. In this dissertation we: 1) provide two adaptive navigation algorithms; 2) develop a coordination mechanism;...
    Resource Type:
    Dissertation
    Full Text:
    ) develop a coordination mechanism; 3) develop a dynamic partnership formation mechanism; and 4

  • Deep Learning for Human and Biological Languages

    Creator:
    Hong, Junki
    Abstract:
    We explore the application of deep learning to the disparate fields of natural language processing and computational biology. Both the sentences uttered by humans as well as the RNA and protein sequences found within the cells of their bodies can be considered formal languages in computer science, as sets of...
    Resource Type:
    Dissertation
    Full Text:
    size greater than 100,000 but in practice usually have less than 20-30 words; RNA sequences have 4

  • Planning in multi-agent partially observable domains using sparse sampling

    Creator:
    Donneau-Golencer, Thierry D.
    Abstract:
    A large number of sequential decision-making problems in uncertain environments can be modeled as Markov Decision Processes (MDPs). In such settings, an agent can observe at each time step the state of the environment and then executes an action, causing a stochastic transition to a new state of the environment...
    Resource Type:
    Masters Thesis
    Full Text:
    ��� ����������������������������������������������������������������������������������������������������������������� T2S �e���)� �����i��4��� ���� �i��@01� "� W &E@0� � U � ���G�l�qu�&E89<�&27+@2-0 "�Z<>��H