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  • Parsing with Recurrent Neural Networks

    Creator:
    Cross, James Henry, III
    Abstract:
    Machine learning models for natural language processing have traditionally relied on large numbers of discrete features, built up from atomic categories such as word forms and part-of-speech labels, which are considered completely distinct from each other. Recently however, the advent of dense feature representations coupled with deep learning techniques has...
    Resource Type:
    Dissertation
    Full Text:
    8, 2016 All Rights Reserved Parsing with Recurrent Neural Networks by James Henry Cross III A

  • Decentralized Multi-Robot Exploration with Sparse Communication through Deep Imitation Learning

    Creator:
    Senewiratne, Yomal K.
    Abstract:
    We present a method for decentralized, multi-robot exploration in adverse environments where communication is minimal. A key conceptual feature of our method is enabling implicit coordination between robots by training a Convolutional Neural Network (CNN) as a heuristic for planning using Monte Carlo Tree Search (MCTS). Our method consists of...
    Resource Type:
    Masters Thesis
    Full Text:
    approved: Geoffrey A. Hollinger We present a method for decentralized, multi-robot exploration in adverse

  • A tool for visualizing sequence alignments and associating annotations

    Creator:
    Zhang, Wenpeng
    Abstract:
    Alignment of genomic sequences from different species is becoming an increasingly powerful method in biology, and is being used for many purposes. The result of sequence alignments is a list of pairs of matched locations between the pattern string and the text string. However, without any proper visualization tools to...
    Resource Type:
    Capstone Project
    Full Text:
    A Tool for Visualizing Sequence Alignments and Associating

  • Theory and Implementation of a Variational Database Management System

    Creator:
    Ataei, Parisa S.
    Abstract:
    In this thesis, I present the variational database management system, a formal framework and its implementation for representing variation in relational databases and managing variational information needs. A variational database is intended to support any kind of variation in a database. Specific kinds of variation in databases have already been...
    Resource Type:
    Dissertation
    Full Text:
    Implementation of a Variational Database Management System Abstract approved: Eric Walkingshaw In this thesis

  • Customizable Visual Traces for Program Explanations

    Creator:
    Bajaj, Divya
    Abstract:
    Correctness and efficiency are important properties of programs. However, to support maintenance and debugging, the programs should also be understandable. Program explanations also play a vital role in educational settings, enhancing the understanding of programs among students. Proof trees provide a sound basis for generating dynamic explanations of programs. But...
    Resource Type:
    Masters Thesis
    Full Text:
    be understandable. Program explanations also play a vital role in educational settings, enhancing

  • Activity recognition in desktop environments

    Creator:
    Shen, Jianqiang
    Abstract:
    Knowledge workers are struggling in the information flood. There is a growing interest in intelligent desktop environments that help knowledge workers organize their daily life. Intelligent desktop environments allow the desktop user to define a set of “activities” that characterize the user’s desktop work. These environments then attempt to identify...
    Resource Type:
    Dissertation
    Full Text:
    struggling in the information flood. There is a growing interest in intelligent desktop environments that

  • Adaptation-based programming

    Creator:
    Bauer, Tim
    Abstract:
    Partial programming is a field of study where users specify an outline or skeleton of a program, but leave various parts undefined. The undefined parts are then completed by an external mechanism to form a complete program. Adaptation-Based Programming (ABP) is a method of partial programming that utilizes techniques from...
    Resource Type:
    Dissertation
    Full Text:
    programming is a field of study where users specify an outline or skeleton of a pro­ gram, but leave various

  • Counterfactual States for Atari Agents via Generative Deep Learning

    Creator:
    Olson, Matthew L.
    Abstract:
    Although deep reinforcement learning agents have produced impressive results in many domains, their decision making is difficult to explain to humans. To address this problem, past work has mainly focused on explaining why an action was chosen in a given state. A different type of explanation that is useful is...
    Resource Type:
    Masters Thesis
    Full Text:
    an action was chosen in a given state. A different type of explanation that is useful is a

  • Deep Convolutional Network on Point Clouds for 3D Scene Understanding

    Creator:
    Wu, Wenxuan
    Abstract:
    As one of the most popular data types, the point cloud is widely used in various appli- cations, including computer vision, computer graphics and robotics. The capability to directly measure 3D point clouds is invaluable in those applications as depth information could remove a lot of the segmentation ambiguities in...
    Resource Type:
    Dissertation
    Full Text:
    in those applications as depth information could remove a lot of the segmentation ambiguities in 2D

  • Toward Disentangling the Activations of the Deep Networks via Low-dimensional Embedding and Non-negative Factorization

    Creator:
    Khorram, Saeed
    Abstract:
    In this thesis, we introduce a novel Explanation Neural Network (XNN) to explain the predictions made by a deep network. The XNN works by embedding a high-dimensional activation vector of a deep network layer non-linearly into a low-dimensional explanation space while retaining faithfulness i.e., the original deep learning predictions can...
    Resource Type:
    Masters Thesis
    Full Text:
    Abstract approved: Fuxin Li In this thesis, we introduce a novel Explanation Neural Network (XNN) to