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Filtering by: Creator Reiff, Steven D. Remove constraint Creator: Reiff, Steven D. Advisor Tadepalli, Prasad Remove constraint Advisor: Tadepalli, Prasad

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  • 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
    Full Text:
    -Dimensional Reinforcement Learning with Human Feedback Abstract approved: William D. Smart Prasad Tadepalli

  • Answer Selection with Attentive Clustering

    Creator:
    Chatterjee, Purbasha
    Abstract:
    Question answering forums like Reddit have been quite effective in improving social interaction and disseminating useful information. Community members ask a variety of questions related to a subject which are answered by other community members. The answers are given ratings by other members. In this thesis we study the problem...
    Resource Type:
    Masters Thesis
    Full Text:
    , 2014; Hu et al, 2014; dos Santos et al, 2015; Wang et al D. N., 2015; Severyn et al, 2015; Tan et al

  • Empirical speedup learning of decomposition rules for planning

    Creator:
    Roncagliolo, Silvana
    Abstract:
    One current research goal of Artificial Intelligence and Machine Learning is to build learning systems that robustly improve their planning performance with experience [Tade91]. This work concentrates on learning decomposition rules, i.e., learning rules that guide the planning process by determining the order in which operators are to be applied...
    Resource Type:
    Capstone Project
    Full Text:
    . Its knowledge is organized as a set of decomposition rules. Each decomposition rule, or d-rule, is

  • 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:
    ′)|(t, t′, e) ∈ E] (2.5) αt = softmax(tanh(Dtwa)) (2.6) ha = D T t αt (2.7) However, having a set of

  • A distributed mixed-integer-programming approach to fair trajectory planning of autonomous systems

    Creator:
    Brahmbhatt, Khushal
    Abstract:
    In a scenario where multiple Unmanned Aerial Vehicles (UAVs) run by different operators are conducting their independent missions in an urban environment, it is important that the limited airspace is shared in a fair manner. Clarity and uniformity in communicating mission specifications to a central controller is also crucial. This...
    Resource Type:
    Capstone Project
    Full Text:
    Definition Consider a D-UAV system where each UAV has a predefined mission starting from an initial

  • Causal Structure Learning from Experiments and Observations

    Creator:
    Sinha, Meghamala
    Abstract:
    In this research, we address the problem of learning a single causal network structure from multiple dataset generated from different experiments. The experiments can be observational or interventional. We assume that each dataset is generated by an unknown causal network altered under different experimental conditions (interventions, manipulation or perturbation). As...
    Resource Type:
    Masters Thesis
    Full Text:
    data from a observational and a interventional experiment d) Network inferred from “Learn and Vote

  • 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
    Full Text:
    reported in Inaguma et al. [46]. Pino et al. [73] use extra D′s,y which includes Librispeech (Ds,x) and

  • 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:
    pruning operator P(D,π) ≡ Pπ(D) for any ADD D and a policy constraint BDD π

  • Monte-Carlo planning for probabilistic domains

    Creator:
    Bjarnason, Ronald V.
    Abstract:
    This thesis presents a progression of novel planning algorithms that culminates in a new family of diverse Monte-Carlo methods for probabilistic planning domains. We provide a proof for performance guarantees and analyze how these algorithms can resolve some of the shortcomings of traditional probabilistic planning methods. The direct policy search...
    Resource Type:
    Dissertation

  • Active learning with committees : an approach to efficient learning in text categorization using linear threshold algorithms

    Creator:
    Liere, Ray
    Abstract:
    We developed and investigated machine learning methods that require minimal preprocessing of the input data, use few training examples, run fast, and still obtain high levels of accuracy. Most approaches to designing machine learning programs are based on the supervised learning paradigm – training examples are chosen randomly and given...
    Resource Type:
    Dissertation