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Filtering by: Creator Pangle, Luke A. Remove constraint Creator: Pangle, Luke A. Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad

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  • Structured learning with latent variables : theory and algorithms

    Creator:
    Zhao, Kai
    Abstract:
    Most tasks in natural language processing (NLP) try to map structured input (e.g., sentence or word sequence) to some form of structured output (tag sequence, parse tree, semantic graph, translated/paraphrased/compressed sentence), a problem known as “structured prediction”. While various learning algorithms such as the perceptron, maximum entropy, and expectation-maximization have...
    Resource Type:
    Dissertation
    Full Text:
    (tag sequence, parse tree, semantic graph, translated/paraphrased/compressed sentence), a problem

  • Learning with Limited Labeled Data in Natural Language Processing

    Creator:
    Obeidat, Rasha
    Abstract:
    The advent of deep learning models leads to a substantial improvement in a wide range of NLP tasks, achieving state-of-art performances without any hand-crafted features. However, training deep models requires a massive amount of labeled data. Labeling new data as a new task or domain emerges consumes time and efforts...
    Resource Type:
    Dissertation
    Full Text:
    advent of deep learning models leads to a substantial improvement in a wide range of NLP tasks

  • Improving and Understanding Deep Models for Natural Language Comprehension

    Creator:
    Ghaeini, Reza
    Abstract:
    Natural Language Comprehension is a challenging domain of Natural Language Processing. To improve a model’s language comprehension/understanding, one approach would be to enrich the structure of the model to enhance its capability in learning the latent rules of the language. In this dissertation, we will first introduce several deep models...
    Resource Type:
    Dissertation
    Full Text:
    . Fern Natural Language Comprehension is a challenging domain of Natural Language Pro- cessing. To

  • Knowledge Base Completion Leveraging Natural Language Data

    Creator:
    Shahbazi, Hamed
    Abstract:
    Information about named entities (real-world objects) is usually harvested from different sources and organized as a multiple relational directed graph in Knowledge Bases (KBs). KBs play essential roles in many NLP modules including question answering, fact-checking, search engines, etc. KBs are big but still incomplete: relational information among entities is...
    Resource Type:
    Dissertation
    Full Text:
    named entities (real-world objects) is usually harvested from differ- ent sources and organized as a

  • Using RUBI to partition agents in air traffic problems with hard constraints and reward shaping

    Creator:
    Curran, William
    Abstract:
    Air traffic flow management over the U.S. airpsace is a difficult problem. Current management approaches lead to hundreds of thousands of hours of delay, costing billions of dollars annually. Weather and airport conditions may instigate this delay, but routing decisions balancing delay with congestion contribute significantly to the propagation of...
    Resource Type:
    Masters Thesis
    Full Text:
    Tumer Air traffic flow management over the U.S. airpsace is a difficult problem. Current man­ agement

  • Multiagent learning for locomotion and coordination in tensegrity robotics

    Creator:
    Iscen, Atil
    Abstract:
    Tensegrity structures are composed of pure compressional elements that are connected via a network of pure tensional elements. The concept of tensegrity promises numerous advantages to the field of robotics. Tensegrity robots are, however, notoriously difficult to control due to their oscillatory nature and nonlinear interaction between the components. Multiagent...
    Resource Type:
    Dissertation
    Full Text:
    are connected via a network of pure tensional elements. The concept of tensegrity promises numerous

  • Deep Learning for Human and Biological Languages

    Creator:
    Hong, Junki
    Abstract:
    We explore the application of deep learning to the disparate fields of natural language processing and computational biology. Both the sentences uttered by humans as well as the RNA and protein sequences found within the cells of their bodies can be considered formal languages in computer science, as sets of...
    Resource Type:
    Dissertation
    Full Text:
    language sentences have a large number of types but a limited sequence of tokens, while nucleotides in

  • Toward computer vision for understanding American football in video

    Creator:
    Hess, Robin W.
    Abstract:
    In this work, I examine the problem of understanding American football in video. In particular, I present several mid-level computer vision algorithms that each accomplish a different sub-task within a larger system for annotating, interpreting, and analyzing collections of American football video. The analysis of football video is useful in...
    Resource Type:
    Dissertation
    Full Text:
    -level computer vision algorithms that each accomplish a different sub-task within a larger system for

  • 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:
    evaluation functions have a number of properties that make them ideal as learning signal, such as sensitiv

  • Semantic embodied navigation : developing agents that navigate from language and vision

    Creator:
    Krantz, Jacob
    Abstract:
    Autonomous robotic agents are on their way to becoming in-home personal assistants, construction assistants, and warehouse workers. The degree of autonomy of such systems is reflected by the manner in which we specify goals to them; the abstraction of low-level commands to high-level goals goes hand-in-hand with increased autonomy. In...
    Resource Type:
    Dissertation
    Full Text:
    - ments to follow a motion path or reach a destination. Semantic refers to how the goal is specified