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Filtering by: Creator Kaiser, Matthew Carl Remove constraint Creator: Kaiser, Matthew Carl Advisor Tadepalli, Prasad Remove constraint Advisor: Tadepalli, Prasad

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  • Domain-Independent Planning for Markov Decision Processes with Factored State and Action Spaces

    Creator:
    Raghavan, Aswin
    Abstract:
    Markov Decision Processes (MDPs) are the de-facto formalism for studying sequential decision making problems with uncertainty, ranging from classical problems such as inventory control and path planning, to more complex problems such as reservoir control under rainfall uncertainty and emergency response optimization for fire and medical emergencies. Most prior research...
    Resource Type:
    Dissertation
    Full Text:
    thankful to Carl Neidner and Coelo Company of Design for providing the dataset of emergencies that oc

  • High-Dimensional Reinforcement Learning with Human Feedback

    Creator:
    Curran, William
    Abstract:
    State-of-the-art personal robots need to perform complex manipulation tasks to be viable in complex scenarios. However, many of these robots, like the PR2, use manipulators with high degrees of freedom. High degrees of freedom are desirable from a functionality standpoint, but make the learning task more difficult by adding a...
    Resource Type:
    Dissertation

  • 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:
    vision and unique perspective. I am grateful for Dr. Matthew Camp- bell’s willingness to be my Graduate

  • 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:
    Empirical Methods in Natural Lan- guage Processing (EMNLP), pages 1532–1543, 2014. [17] Matthew E. Peters

  • Local and Global Explanations for Deep Image Classification via Structured Attention Graphs

    Creator:
    Shitole, Vivswan
    Abstract:
    Attention maps are popular tools of explaining the decisions of convolutional neural net-works (CNNs) for image classification. Typically, for each image of interest, a single attention map is produced, which assigns weights to pixels based on their importance to the classification. We argue that a single attention map provides an...
    Resource Type:
    Masters Thesis

  • Explaining and Improving Neural Machine Translation

    Creator:
    Yang, Yilin
    Abstract:
    Machine Translation, the task of automatically translating between human languages has been studied for decades. This task is used to be solved by count-based statistical models, e.g. Phrase-based Statistical Machine Translation (PBSMT), which solves the translation problem by separately training a statistical language model and a translation model. Recently, Neural...
    Resource Type:
    Dissertation
    Full Text:
    Zheng, Qi Lyu, Jun li, Anurag Koul, Matthew Olson, Juneki Hong, Neale Ratzlaff, Yiren Wang, Jie hao

  • Towards Direct Simultaneous Speech Translation

    Creator:
    Chen, Junkun
    Abstract:
    Simultaneous speech translation (SimulST) is widely useful in many cross-lingual communication scenarios, including multinational conferences and international traveling. Since text-based simultaneous machine translation (SimulMT) has achieved great success in recent years. The conventional cascaded approach for SimulST uses a pipeline of streaming ASR followed by simultaneous MT but suffers from...
    Resource Type:
    Dissertation