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Filtering by: Creator Meigs, Andrew J. Remove constraint Creator: Meigs, Andrew J. Committee Member Wong, Weng-Keen Remove constraint Committee Member: Wong, Weng-Keen Degree Name Master of Science (M.S.) Remove constraint Degree Name: Master of Science (M.S.)

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  • A study of methods for fine-grained object classification of arthropod specimens

    Creator:
    Lin, Junyuan
    Abstract:
    Object categorization is one of the fundamental topics in computer vision research. Most current work in object categorization aims to discriminate among generic object classes with gross differences. However, many applications require much finer distinctions. This thesis focuses on the design, evaluation and analysis of learning algorithms for fine- grained...
    Resource Type:
    Masters Thesis
    Full Text:
    the within-cluster scatter is defined as min µk,cj J = M∑ j=1 K∑ k=1 cjk‖xj − µk‖22. The

  • Revisiting output coding for sequential supervised learning

    Creator:
    Hao, Guohua
    Abstract:
    Markov models are commonly used for joint inference of label sequences. Unfortunately, inference scales quadratically in the number of labels, which is problematic for training methods where inference is repeatedly preformed and is the primary computational bottleneck for large label sets. Recent work has used output coding to address this...
    Resource Type:
    Masters Thesis
    Full Text:
    unknown 9 distribution P (x, y), that is, ∆m(xi, yi) = [ − ∂ ∂Ψ(xi, yi) ∑ j `(xj, yj, Ψ(xj, yj

  • Open Set Learning with Counterfactual Images

    Creator:
    Neal, Lawrence W.
    Abstract:
    In open set recognition, a classifier must label instances of known classes while detecting instances of unknown classes not encountered during training. To detect unknown classes while still generalizing to new instances of existing classes, this thesis introduces a dataset augmentation technique called counterfactual image generation. This approach, based on...
    Resource Type:
    Masters Thesis
    Full Text:
    examples. Given a mean activation vector for each class j ∈ [1...K], a Weibull distribution with values (τ

  • Classifier Chains for Multi-Label Classification with Incomplete Labels

    Creator:
    Almuallim, Jafer
    Abstract:
    Many methods have been explored in the literature of multi-label learning, ranging from simple problem transformation to more complex method that capture correlation among labels. However, mostly all existing works do not address the challenge with incomplete label data. The goal of this project is to extend the work of...
    Resource Type:
    Capstone Project
    Full Text:
    number of labels associated with an instance defined as followed: Lcard = 1 N ∑N i=1 ∑L j=1 ti 1http

  • Adversarial Attacks in Natural Language Question-Answering

    Creator:
    Rahurkar, Prachi S.
    Abstract:
    Question Answering in natural language processing has achieved significant progress in recent years. Yet, training and testing set methodology to evaluate the language models has proved inadequate. Adversarial examples aid us in finding loopholes inside these models and provide insights into their inner workings. In this work, an evaluation based...
    Resource Type:
    Masters Thesis
    Full Text:
    computer vision: A survey. IEEE Access, 6:14410–14430, 2018. [2] Anish Athalye, Logan Engstrom, Andrew

  • UCT for tactical assault battles in real-time strategy games

    Creator:
    Balla, Radha-Krishna
    Abstract:
    We consider the problem of tactical assault planning in real-time strategy games where a team of friendly agents must launch an assault on an enemy. This problem offers many challenges including a highly dynamic and uncertain environment, multiple agents, durative actions, numeric attributes, and different optimization objectives. While the dynamics...
    Resource Type:
    Masters Thesis

  • Toward end-user debugging of machine-learned programs

    Creator:
    Kulesza, Todd
    Abstract:
    The results of a machine learning from user behavior can be thought of as a program, and like all programs, it may need to be debugged. Providing ways for the user to debug it matters because without the ability to fix errors, users may find that the learned program’s errors...
    Resource Type:
    Masters Thesis
    Full Text:
    me to have been a constant source of inspiration and encouragement. Dr. Andrew Ko provided many

  • Toward Disentangling the Activations of the Deep Networks via Low-dimensional Embedding and Non-negative Factorization

    Creator:
    Khorram, Saeed
    Abstract:
    In this thesis, we introduce a novel Explanation Neural Network (XNN) to explain the predictions made by a deep network. The XNN works by embedding a high-dimensional activation vector of a deep network layer non-linearly into a low-dimensional explanation space while retaining faithfulness i.e., the original deep learning predictions can...
    Resource Type:
    Masters Thesis
    Full Text:
    M ,S 1 2 ‖X −MS‖2F (2.8) subject to Mij ≥ 0, Sij ≥ 0 ∀i, j where r is the decomposition rank and

  • Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms

    Creator:
    Ibrahim, Shahana
    Abstract:
    Crowdsourcing is a popular paradigm to address the high demands for labeled data in big data deluge. It aims to produce accurate labels by effectively integrating noisy, non-expert labeling from crowdsourced workers (annotators). The machine learning community has been studying effective crowdsourcing methods for many years, and many models and...
    Resource Type:
    Masters Thesis
    Full Text:
    , for a reasonable annotator `, Pr(X` = j|Y = j) should be fairly greater than Pr(X` = j|Y = k) and Pr(X