Search Constraints

Start Over
Filtering by: Creator Campbell, H. F. Remove constraint Creator: Campbell, H. F. Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad Degree Level Master's Remove constraint Degree Level: Master's

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

  • Scale effects on reinforced concrete beams strengthened for shear with discrete externally bonded carbon fiber-reinforced polymer U-wraps

    Creator:
    Dawson, Matthew Ryan
    Abstract:
    Current ACI design provisions for shear in reinforced concrete (RC) beams strengthened with externally bonded carbon fiber-reinforced polymer (CFRP) U-wraps may not adequately account for the effect of scale. This paper describes tests of 6 geometrically scaled beams to identify possible scale effects of such beams. Results indicated that effective...
    Resource Type:
    Masters Thesis
    Full Text:
    Specimens1 Six specimens at three scales (F = full, H = half, and Q = quarter scale) were used in a

  • Re-understanding Finite-State Representations of Recurrent Policy Networks

    Creator:
    Danesh, Mohamad H.
    Abstract:
    We propose an approach for understanding control policies represented as recurrent neural networks. Recent work has approached this problem by transforming such recurrent policy networks into finite-state machines (FSM) and then analyzing the equivalent minimized FSM. While this led to interesting insights, the minimization process can obscure a deeper understanding...
    Resource Type:
    Masters Thesis
    Full Text:
    n in g A ft er M in im iz at io n N h N o D ec is . P o in ts S ta te s O b s. P er f

  • D₊₊ : Structural Credit Assignment in Tightly Coupled Multiagent Domains

    Creator:
    Rahmattalabi, Aida
    Abstract:
    Autonomous multiagent teams can be used in complex exploration tasks to both expedite the exploration and improve the efficiency. However, use of multiagent systems presents additional challenges. Specifically, in domains where the agents' actions are tightly coupled, coordinating multiple agents to achieve cooperative behavior at the group level is difficult....
    Resource Type:
    Masters Thesis
    Full Text:
    using a fitness function, F (z), and assigned to every agent in the team. In this paper, we propose D

  • Heuristic search in symbolic probability inference

    Creator:
    Pan, Yonghong
    Abstract:
    I present a new heuristic search approach to compute approximate answers for the probability query in belief nets. This approach can compute the 'best' bounds for a query in a period of any given time (if time permitted, it will get an exact value). It inherits the essence of Symbolic...
    Resource Type:
    Capstone Project
    Full Text:
    algorithms. 7. Reference [Chin, H. L. and G. F. Cooper, 1987]. Stochastic Simulation of Bayesian Belief

  • Novelty Detection Under the Multi-Instance Multi-Label Framework

    Creator:
    Lou, Qi
    Abstract:
    Novelty detection plays an important role in machine learning and signal processing. This project studies novelty detection in a new setting where the data object is represented as a bag of instances and associated with multiple class labels, referred to as multi-instance multi-label (MIML) learning. Contrary to the common assumption...
    Resource Type:
    Capstone Project
    Full Text:
    labels. In the traditional MIML applications the goal is to learn a bag-level classifier f : 2X → 2Y

  • Separabilities for a new class of gray codes

    Creator:
    Park, Jung Pil
    Resource Type:
    Capstone Project
    Full Text:
    n-digit distance Gray code over Z4 under the mapping f: Z4 --+ ZJ such that 0-+ 00, 1-+ 01, 2-+ 11

  • Shrunken learning rates do not improve AdaBoost on benchmark datasets

    Creator:
    Forrest, Daniel L. K.
    Abstract:
    Recent work has shown that AdaBoost can be viewed as an algorithm that maximizes the margin on the training data via functional gradient descent. Under this interpretation, the weight computed by AdaBoost, for each hypothesis generated, can be viewed as a step size parameter in a gradient descent search. Friedman...
    Resource Type:
    Masters Thesis
    Full Text:
    , from an unknown distribution P(x, y), we want to find a function F, where F(x) = y, that minimizes the

  • Towards reliable and survivable ocean wave energy converters

    Creator:
    Brown, Adam C.
    Abstract:
    Ocean wave energy is a new and developing field of renewable energy with great potential. The energy contained in one meter of an average wave off the coast of Newport Oregon could supply dozens of homes with electricity. However, ocean waves are usually quite irregular which leads to large bursts...
    Resource Type:
    Masters Thesis
    Full Text:
    .” John F. Kennedy, June 28, 1963 Robyn, I’m sure he meant to say women too. CONTRIBUTION OF

  • 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:
    , where we set P = C0. Given a frame F and its projection F̃ on P via H, let P(F̃ ) be the sub-region on