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Filtering by: Creator Hadley, Adam S. Remove constraint Creator: Hadley, Adam S. Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad

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  • Coordination for Scalable Multiple Robot Planning Under Temporal Uncertainty

    Creator:
    Marcon dos Santos, Gilberto
    Abstract:
    This dissertation incorporates coalition formation and probabilistic planning towards a domain-independent automated planning solution scalable to multiple heterogeneous robots in complex domains. The first research direction investigates the effectiveness of Task Fusion and introduces heuristics that improve task allocation and result in better quality plans, while requiring lower computational cost...
    Resource Type:
    Dissertation

  • Towards reliable and survivable ocean wave energy converters

    Creator:
    Brown, Adam C.
    Abstract:
    Ocean wave energy is a new and developing field of renewable energy with great potential. The energy contained in one meter of an average wave off the coast of Newport Oregon could supply dozens of homes with electricity. However, ocean waves are usually quite irregular which leads to large bursts...
    Resource Type:
    Masters Thesis
    Full Text:
    OF THE THESIS OF Adam C Brown for the degree of Master of Science in Mechanical Engineering

  • A numerical approach to Tamme's problem in euclidean n-space

    Creator:
    Adams, Patrick Guy
    Resource Type:
    Masters Thesis
    Full Text:
    points on the surface of a unit sphere, Sn (=S'1), embedded in the euclidean space WI (n an integer) so

  • Advancing Power Grid Computing: Analysis and Synthesis of Wide-Area Data, Distributed Real-Time Hardware-In-the-Loop Simulations, and Machine Learning for Event Detection

    Creator:
    Hagan, Travis
    Abstract:
    Global Positioning Systems have allowed for precise timing of power system measurements over wide areas. This newly found capability has the potential to provide much greater insight into the operation of the power system and its response to contingencies, but few analytical techniques currently exist that provide enough robustness and...
    Resource Type:
    Dissertation
    Full Text:
    &--*",'-&'4)&$2-1%4,+*",)-*+!$)-/+$!$%&-"**<%(KOPN7Q1%4,+*",)-*+2)&) '-($%$+)&$2:1R,)-*+S$)-/+$!$%&T%'&-FRST

  • A Distributed Scheme for Accelerating and Scaling PSPNet

    Creator:
    Krishna, Ajay
    Abstract:
    Advances in deep learning based image processing have led to their adoption for a wide range of applications, and in tow with these developments is a dramatic increase in the availability of high quality datasets. With this comes the need to accelerate and scale deep learning applications in order to...
    Resource Type:
    Masters Thesis
    Full Text:
    levels Pre-process (s) Deep learning (s) Image combine (s) Total (s) 4 1.72 29.29 28.61 59.62 3 1.30

  • Simulator-Defined MDP Planning with Applications in Natural Resource Management

    Creator:
    Alkaee Taleghan, Majid
    Abstract:
    This work is inspired by problems in natural resource management centered on the challenge of invasive species. Computing optimal management policies for maintaining ecosystem sustainable is challenging. Many ecosystem management problems can be formulated as MDP (Markov Decision Process) planning problems. In a simulator-defined MDP, the Markovian dynamics and rewards...
    Resource Type:
    Dissertation
    Full Text:
    Fiechter(s0, γ, F, �, δ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2 UPPERP(s, a, δ

  • Learning and Improving Policies for Probabilistic Planning Problems

    Creator:
    Issakkimuthu, Murugeswari
    Abstract:
    In this work, we study the problem of learning and improving policies for probabilistic planning problems. In the first part, we train neural network policies for probabilistic planning problems modeled as factored Markov decision problems. The objective is to train problem-specific neural networks via supervised learning to imitate the action...
    Resource Type:
    Dissertation
    Full Text:
    , Prof. N. S. Narayanaswamy and Prof. Deepak Khemani at IIT Madras, and Prof. Anselm Blumer at Tufts

  • Event detection with forward-backward recurrent neural networks

    Creator:
    Ghaeini, Mohammad Reza
    Abstract:
    Automatic event extraction from natural text is an important and challenging task for natural language understanding. Traditional event detection methods heavily rely on manually engineered rich features. Recent deep learning approaches alleviate this problem by automatic feature engineering. But such efforts, like tradition methods, have so far only focused on...
    Resource Type:
    Masters Thesis
    Full Text:
    which apply Convolutional Neural Networks (CNN s) to a window of text around potential triggers 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:
    , ...yn] of referent entities to maximize the following score: s(Y) = n∑ i=1 ψ(xi, yi) + n∑ i=1 n∑ j=1

  • 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:
    ) label scores of the resulting span: ξ = maxX s(j, j+1, X) and σ = maxX s(k, j,X) where X is a