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Filtering by: Creator Plantinga, Andrew J. Remove constraint Creator: Plantinga, Andrew J. Committee Member Fern, Xiaoli Remove constraint Committee Member: Fern, Xiaoli

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  • Towards Narrative Understanding with Deep Neural Networks and Hidden Markov Models

    Creator:
    Orr, J. Walker
    Abstract:
    Narratives are central to communication and the human experience. For a computer system to understand a narrative, it must be able to identify the key facts or plot elements that describe what happened or how the world has changed. These element are called events;establishing a document’s events and the relationships...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF J. Walker Orr for the

  • 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

  • Exploration of regression models for cancer noncoding mutation recurrence

    Creator:
    Xu, Tanjin
    Abstract:
    An important impact of the genome technology revolution will be the elucidation of mechanisms of cancer pathogenesis, leading to improvements in the diagnosis of cancer and the selection of cancer treatment. Integrated with current well-studied massive knowledge and findings about the role of protein-coding mutations in cancer, demystifying the functional...
    Resource Type:
    Masters Thesis
    Full Text:
    ) to pseudo-residuals. Let J be the number of the 20 tree’s leaves. The tree partitions the feature

  • Near-contact Grasping Strategies: Improve Robotic Grasping from Awkward Poses with Deliberate Finger Motion

    Creator:
    Ong, Yi Herng
    Abstract:
    As robots are becoming more relevant to our lives, they are still having hard time accomplishing simple tasks such as picking and lifting. Problems that include environmental constraints, pose uncertainties and hardware noises restrain robots for grasping an object successfully from a perceivable environment. Many have looked into finding best...
    Resource Type:
    Masters Thesis

  • Semantic image segmentation using domain constraints

    Creator:
    Roy, Anirban
    Abstract:
    This dissertation addresses the problem of semantic labeling of image pixels. In the course of our work, we considered different types of semantic labels, including object classes (e.g., car, person), 3D depth values (in the range 0 to 80 meters), and affordance classes (e.g., walkable, sittable). Semantic pixel labeling is...
    Resource Type:
    Dissertation
    Full Text:
    pixel i and a window at neighboring pixel j have simi- lar depths, but are different in appearance

  • 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

  • A statistical inference framework for finding recurring patterns in large data with applications to energy management

    Creator:
    You, Zeyu
    Abstract:
    We consider the problem of finding unknown patterns that are recurring across multiple sets. For example, finding multiple objects that are present in multiple images or a short DNA code that is repeated across multiple DNA sequences. We first consider a simple problem of finding a single unknown pattern in...
    Resource Type:
    Masters Thesis
    Full Text:
    only with respect to τ min τ N∑ i=1 ‖Yieτi − 1 N N∑ j=1 Yjeτj‖2 + N∑ i=1 φi(τi). (2.6) While

  • Computational Elucidation of the Regulatory SNPs in the Non-Coding Regions of the Human Genome

    Creator:
    Yao, Yao
    Abstract:
    We describe a series of novel computational models, CERENKOV (Computational Elucidation of the REgulatory NonKOding Variome) and its successors CERENKOV2, CERENKOV3, and Convolutional CERENKOV3, for discriminating regulatory single nucleotide polymorphisms (rSNPs) from non-regulatory SNPs within non-coding genetic loci. The CERENKOV models are designed for recognizing rSNPs in the context of...
    Resource Type:
    Dissertation

  • 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

  • Rare category detection using hierarchical mean shift

    Creator:
    Vatturi, Pavan Kumar
    Abstract:
    Many applications in surveillance, monitoring, scientific discovery, and data cleaning require the identification of anomalies. Although many methods have been developed to identify statistically significant anomalies, a more difficult task is to identify anomalies that are both interesting and statistically significant. Category detection is an emerging area of machine learning...
    Resource Type:
    Masters Thesis
    Full Text:
    ][n]) = SemiSupervisedEM (S, Labels);3 where PointOwnership[i][j] is an estimate of the degree of