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Filtering by: Creator Triska, F. J. Remove constraint Creator: Triska, F. J. Committee Member Fern, Alan Remove constraint Committee Member: Fern, Alan

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  • Methods for Detection and Recovery of Out-of-Distribution Examples

    Creator:
    Ratzlaff, Neale J.
    Abstract:
    Deep neural networks currently comprise the backbone of many applications where safety is a critical concern, for example: autonomous driving and medical diagnostics. Unfortunately these systems currently fail to detect out-of-distribution (OOD) inputs and can be prone to making dangerous errors when exposed to them. In addition, these same systems...
    Resource Type:
    Masters Thesis
    Full Text:
    at their most simplistic are used to approximate some arbitrary function f . For instance, a

  • Usable and Scalable Querying of Scientific Datasets

    Creator:
    McCamish, Benjamin J.
    Abstract:
    Scientists and engineers have to analyze and query multiple large databases. Analysis over databases created by phasor measurement units can provide insight into the health of the grid, thereby improving control over operations. Realizing this data-driven control, however, requires validating, processing and storing massive amounts of PMU data efficiently, which...
    Resource Type:
    Dissertation
    Full Text:
    ,j = 1, if the ith record falls into the specified value and range of the jth bin, and bi,j = 0

  • Bayesian optimization with empirical constraints

    Creator:
    Azimi, Javad
    Abstract:
    Bayesian Optimization (BO) methods are often used to optimize an unknown function f(•) that is costly to evaluate. They typically work in an iterative manner. In each iteration, given a set of observation points, BO algorithms select k ≥ 1 points to be evaluated. The results of those points are...
    Resource Type:
    Dissertation
    Full Text:
    (BO) methods are often used to optimize an unknown function f(·) that is costly to evaluate. They

  • 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:
    <" "��8(&27s�F/G@0�+/��9�! \�+/�@J&2/�*C� -0HJI�1G<"�! ���8!���!/�89� $.�(&E/,-E:b<"���l46 "&2*�1^&E<"�l

  • Revenue-based spectrum management via Markov decision process

    Creator:
    Zhu, Pingan
    Abstract:
    We consider the problem of wireless spectrum management in cognitive wireless networks that maximizes the revenue for a spectrum operator. Specifically, we study the problem on how a wireless spectrum operator can optimally allocate its limited spectrum to various classes users/devices who pay differently for their spectrum per unit time....
    Resource Type:
    Masters Thesis
    Full Text:
    be leaving the system and 11 a probability βj that the new user of application class j will

  • Weakly Supervised Learning for Activity Recognition from Time Series Data

    Creator:
    Guan, Xinze
    Abstract:
    The thesis focuses on activity recognition from sensor data, which has spurred a great deal of interest due to its impact on health care and security. Previous work on activity recognition from multivariate time series data has mainly applied supervised learning techniques which require a high degree of annotation effort...
    Resource Type:
    Dissertation
    Full Text:
    . Correlation between each pair of axes:∑T i=1(si−µs)(vi−µv)√∑T i=1(si−µs) ∑T j=1(vj−µv) . O(N) Table 2.1

  • Efficient Incremental Panorama Reconstruction from Multiple Videos

    Creator:
    Feng, Zhongyuan
    Abstract:
    Constructing a panorama from a set of videos is a long-standing problem in computer vision. A panorama represents an enhanced still-image representation of an entire scene captured in a set of videos, where each video shows only a part of the scene. Importantly, a panorama shows only the scene background,...
    Resource Type:
    Capstone Project
    Full Text:
    Estimation Given an image pair Ii, Ij , as well as matched features f m i ,f n j indexed by m,n respec

  • Principles of Variational Databases

    Creator:
    Ataei, Parisa S.
    Abstract:
    Data variations are prevalent in real-world applications. For example, software vendors have to handle numerous variations in the business requirements, conventions, and environmental settings of a software product. In database-backed software, the database of each version may have a different schema and content. As another example, data scientists often need...
    Resource Type:
    Masters Thesis
    Full Text:
    : F J.K : F → C→ B F JbKc = b F JfKc = c f F J¬fKc = ¬F JfKc F Jcl1 ∧ cl2Kc = F Jcl1Kc ∧ F Jcl2Kc F

  • Customizable Visual Traces for Program Explanations

    Creator:
    Bajaj, Divya
    Abstract:
    Correctness and efficiency are important properties of programs. However, to support maintenance and debugging, the programs should also be understandable. Program explanations also play a vital role in educational settings, enhancing the understanding of programs among students. Proof trees provide a sound basis for generating dynamic explanations of programs. But...
    Resource Type:
    Masters Thesis
    Full Text:
    : x * x⇓ 25 f x=5 : x⇓ 5x h x=5 ∈ x=5 k 5*5 = 25 j Figure 4.4: Proof DAG for let sqr=\x->x*x in

  • Uncertainty in Deep Learning with Implicit Neural Networks

    Creator:
    Ratzlaff, Neale
    Abstract:
    The ability to extract uncertainties from predictions is crucial for the adoption of deep learning systems to safety-critical applications. Uncertainty estimates can be used as a failure signal, which is necessary for automating complex tasks where safety is a concern. Furthermore, current deep learning systems do not provide uncertainty estimates,...
    Resource Type:
    Dissertation
    Full Text:
    covariance, and input to layer-wise generators {f1, · · · , fL}. Each generator fj outputs parameters θj for