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Filtering by: Creator Mahaffee, W. F. Remove constraint Creator: Mahaffee, W. F. Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad

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  • 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:
    the Battery of Algorithms . . . . . . . . . . . . . . . 105 F Corpus Evaluation Supplement

  • A C* development environment for the Meiko CS-2 multicomputer

    Creator:
    Zhang, Chung
    Abstract:
    With sequential computing technology reaching its speed limits, parallel processing is emerg­ing as the key to very-high-speed computation. However, developing a parallel program is by no means a simple task; neither is analyzing the performance of parallel programs. C* is a high-level data-parallel language that hides explicit message passing and...
    Resource Type:
    Capstone Project
    Full Text:
    6 processors . Th e ne w im ple mentati on The scatter and gather algorithms of the UNH version

  • A Distributed Scheme for Accelerating and Scaling PSPNet

    Creator:
    Krishna, Ajay
    Abstract:
    Advances in deep learning based image processing have led to their adoption for a wide range of applications, and in tow with these developments is a dramatic increase in the availability of high quality datasets. With this comes the need to accelerate and scale deep learning applications in order to...
    Resource Type:
    Masters Thesis
    Full Text:
    , W. Dong, R. Socher, L. Li, Kai Li, and Li Fei-Fei. Imagenet: A large- scale hierarchical image

  • A factoring approach for probabilistic inference in belief networks

    Creator:
    Li, Zhaoyu
    Abstract:
    Reasoning about any realistic domain always involves a degree of uncertainty. Probabilistic inference in belief networks is one effective way of reasoning under uncertainty. Efficiency is critical in applying this technique, and many researchers have been working on this topic. This thesis is the report of our research in this...
    Resource Type:
    Dissertation
    Full Text:
    MPE for nodes b and c. 89 10. The evaluation tree of querying p(e) given f = 1 in the simple belief

  • A General Purpose Agent-Based Blackboard Optimization Method Applied to Sodium Fast Reactor Design and Analysis

    Creator:
    Stewart, Ryan H.
    Abstract:
    We present a novel multi-objective optimization methodology built upon a multi-agent blackboard framework. This multi-agent blackboard system (MABS) synthesizes blackboard architectures, multi-agent environments, and optimization theory. The blackboard architecture creates the framework for initializing, storing, and solving a multi-objective optimization problem. Multiple agents allow for an optimization problem to be...
    Resource Type:
    Dissertation
    Full Text:
    culminate the objective functions into a single objective vector (F(x)) to denote a design (or solution

  • A numerical approach to Tamme's problem in euclidean n-space

    Creator:
    Adams, Patrick Guy
    Resource Type:
    Masters Thesis
    Full Text:
    -known lower bounds for m < 90 on S3. 5 Other recent work has been contributed by P. W. Fowler and T

  • A SAT-based planning framework for optimizing resource production

    Creator:
    Ventura, Christopher
    Abstract:
    Domain-independent automated planning is concerned with computing a sequence of actions that can transform an initial state into a desired goal state. Resource production domains form an interesting class of such problems, in that they typically require reasoning about concurrent durative-actions with continuous effects while minimizing some cost function. Although...
    Resource Type:
    Masters Thesis

  • A Study of Temporal Convolutional Neural Networks for Music Language Modeling as Applied to Automatic Music Transcription

    Creator:
    Meyn, Matthew
    Abstract:
    Automatic music transcription (AMT) is the task, given an acoustic representation of music, to recover a symbolic notation of the written notes expressed by the sound. Transcribing music with multiple notes sounding simultaneously is difficult for both humans and machines. Much existing work on AMT has focused on suitable acoustic...
    Resource Type:
    Capstone Project
    Full Text:
    building models that can estimate the likelihood P (Ŵ ) of a possible sequence of tokens Ŵ = 〈ŵ1, ŵ2

  • Action Segmentation in Videos: Deep Models, Prediction Diffusion, and Deep-Temporal Augmentations

    Creator:
    Aziere, Nicolas
    Abstract:
    This paper addresses the high model complexity and overconfident frame labeling of state-of-the-art (SOTA) action segmenters. Their complexity is typically justified by the need to sequentially refine action segmentation through multiple stages of a deep architecture. However, this multistage refinement does not take into account uncertainty of frame labeling predicted...
    Resource Type:
    Dissertation
    Full Text:
    standard MSA parameters, the hybrid MSA also learns the convolution filter wc and compression parameters W

  • Active learning of constraints for semi-supervised clustering

    Creator:
    Xiong, Sicheng
    Abstract:
    Semi-supervised clustering aims to improve clustering performance by considering user supervision in the form of pairwise constraints. In this paper, we study the active learning problem of selecting pairwise must-link and cannot-link constraints for semisupervised clustering. We consider active learning in an iterative manner where in each iteration queries are...
    Resource Type:
    Masters Thesis
    Full Text:
    Comparison on F-measure (mean ± std). The best performance and its comparable performances based on paired t