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Filtering by: Creator Meigs, Andrew J. Remove constraint Creator: Meigs, Andrew J. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science Committee Member Wong, Weng-Keen Remove constraint Committee Member: Wong, Weng-Keen

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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

  • Efficient training and feature induction in sequential supervised learning

    Creator:
    Hao, Guohua
    Abstract:
    Sequential supervised learning problems arise in many real applications. This dissertation focuses on two important research directions in sequential supervised learning: efficient training and feature induction. In the direction of efficient training, we study the training of conditional random fields (CRFs), which provide a flexible and powerful model for sequential...
    Resource Type:
    Dissertation
    Full Text:
    as P (xt|yt) = ∏ j P (xt,j|yt) . This assumption of independence of each input feature xt,j

  • New Directions in Search-based Structured Prediction: Multi-Task Learning and Integration of Deep Models

    Creator:
    Ma, Chao
    Abstract:
    This thesis studies the problem of structured prediction (SP), where the agent needs to predict a structured output for a given structured input (e.g., Part-of-Speech tagging sequence for an input sentence). Many important applications including machine translation in natural language processing (NLP) and image interpretation in computer vision can be...
    Resource Type:
    Dissertation
    Full Text:
    of their occurrence in the document. Each output variable vij (i < j) corresponds to a coreferent

  • 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:
    captured by: J(Q) = E(x1,···,x|Q|) [ E(y1,···,y|Q|) [ max { y1, . . . , y|Q| } ∣∣∣D, (x1, · · ·, x|Q

  • 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

  • Generative Models Meet Explainable AI and Long-Tail Learning: from Attribution Maps to Image Synthesis

    Creator:
    Khorram, Saeed
    Abstract:
    The advancement of artificial intelligence (AI) has led to transformative developments across multiple sectors, fostering innovation and redefining our interactions with technology. As AI matures and becomes integrated into society, it offers numerous opportunities to address global challenges and revolutionize a wide array of human endeavors. These advances are driven...
    Resource Type:
    Dissertation
    Full Text:
    , Ario, Nima, Reza, Mohammadreza, Mélissa, Andrew, Sarah, Nicolas, Amirali, and Armin. Their