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  • 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
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    produces a probability distribution over actions, P (a|s), which we will denote by the vector P̂ (s). Given

  • Incorporating and Learning Behavior Constraints for Sequential Decision Making

    Creator:
    Pinto, Jervis
    Abstract:
    Writing a program that performs well in a complex environment is a challenging task. In such problems, a method of deterministic programming combined with reinforcement learning (RL) can be helpful. However, current systems either force developers to encode knowledge in very specific forms (e.g., state-action features), or assume advanced RL...
    Resource Type:
    Dissertation
    Full Text:
    Problems (MDPs) In the setting considered here, an MDP [52] is a tuple (S,A, P,R), where S is a finite set

  • Data Collection in Sensor Networks via the Novel Fast Markov Decision Process Framework

    Creator:
    Duong, Thai
    Abstract:
    We investigate the data collection problem in sensor networks. The network consists of a number of stationary sensors deployed at different sites for sensing and storing data locally. A mobile element moves from sites to sites to collect data from the sensors periodically. There are different costs associated with the...
    Resource Type:
    Masters Thesis
    Full Text:
    of the system, a set of control actions A, a transition probability matrix P|S|×|S|, and a reward

  • Adiabatic Markov Decision Process : convergence of value iteration algorithm

    Creator:
    Duong, Thai
    Abstract:
    Markov Decision Process (MDP) is a well-known framework for devising the optimal decision making strategies under uncertainty. Typically, the decision maker assumes a stationary environment which is characterized by a time-invariant transition probability matrix. However, in many real-world scenarios, this assumption is not justified, thus the optimal strategy might not...
    Resource Type:
    Masters Thesis
    Full Text:
    : Assumption 1. The reward r(s,a) and the probability p( j|s,a) are stationary. Assumption 2. The reward r(s

  • Re-understanding Finite-State Representations of Recurrent Policy Networks

    Creator:
    Danesh, Mohamad H.
    Abstract:
    We propose an approach for understanding control policies represented as recurrent neural networks. Recent work has approached this problem by transforming such recurrent policy networks into finite-state machines (FSM) and then analyzing the equivalent minimized FSM. While this led to interesting insights, the minimization process can obscure a deeper understanding...
    Resource Type:
    Masters Thesis
    Full Text:
    an d A ta ri en v ir on m en ts . G am e Q B N S iz es O ri gi n al M M A ft er P ru

  • New learning modes for sequential decision making

    Creator:
    Judah, Kshitij
    Abstract:
    This thesis considers the problem in which a teacher is interested in teaching action policies to computer agents for sequential decision making. The vast majority of policy learning algorithms o er teachers little flexibility in how policies are taught. In particular, one of two learning modes is typically considered: 1)...
    Resource Type:
    Dissertation
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    Modes for Sequential Decision Making Abstract approved: Alan P. Fern This thesis considers the

  • 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
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    Vision for Understanding American Football in Video Abstract approved: Alan P. Fern In this work, I

  • Scheduling and Online Planning in Stochastic Diffusion Networks

    Creator:
    Xue, Shan
    Abstract:
    Diffusion processes in networks are common models for many domains, including species colonization, information/idea cascade, disease propagation and fire spreading. In diffusion networks, a diffusion event occurs when a behavior spreads from one node to the other following a probabilistic model, where the behavior could be species, an idea, a...
    Resource Type:
    Dissertation
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    Online Planning in Stochastic Diffusion Networks Abstract approved: Alan P. Fern Diffusion processes

  • Adversarial planning by strategy switching in a real-time strategy game

    Creator:
    King, Brian D.
    Abstract:
    We consider the problem of strategic adversarial planning in a Real-Time Strategy (RTS) game. Strategic adversarial planning is the generation of a network of high-level tasks to satisfy goals while anticipating an adversary's actions. In this thesis we describe an abstract state and action space used for planning in an...
    Resource Type:
    Masters Thesis
    Full Text:
    : Adversarial Planning by Strategy Switching in a Real-Time Strategy Game Abstract approved: Alan P. Fern We

  • Optimization of seasonal irrigation scheduling by genetic algorithms

    Creator:
    Canpolat, Necati
    Abstract:
    In this work, we first introduce a novel approach to the long term irrigation scheduling using Genetic Algorithms (GAs). We explore the effectiveness of GAs in the context of optimizing nonlinear crop models and describe application requirements and implementation of the technique. GAs were found to converge quickly to near-optimal...
    Resource Type:
    Dissertation
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    Genetic Algorithms. Abstract approved: John P. Bolte In this work, we first introduce a novel approach

  • OME : A Framework for Running Spatially Explicit System Dynamics Models

    Creator:
    Wingo, Patrick C.
    Abstract:
    The Open Modeling Environment (OME) is a tool developed to address some known shortcomings in ecological System Dynamics (SD) modeling research. OME provides a common set of methods for interacting directly with spatial information, reducing the need for modelers to create their own methods for doing so. The environment is...
    Resource Type:
    Masters Thesis
    Full Text:
    Framework for Running Spatially Explicit System Dynamics Models. Abstract approved: John P. Bolte

  • A General Purpose Agent-Based Blackboard Optimization Method Applied to Sodium Fast Reactor Design and Analysis

    Creator:
    Stewart, Ryan H.
    Abstract:
    We present a novel multi-objective optimization methodology built upon a multi-agent blackboard framework. This multi-agent blackboard system (MABS) synthesizes blackboard architectures, multi-agent environments, and optimization theory. The blackboard architecture creates the framework for initializing, storing, and solving a multi-objective optimization problem. Multiple agents allow for an optimization problem to be...
    Resource Type:
    Dissertation
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    Abstract approved: Todd S. Palmer We present a novel multi-objective optimization methodology built upon

  • Monte Carlo Tree Search with Fixed and Adaptive Abstractions

    Creator:
    Hostetler, Jesse A.
    Abstract:
    Monte Carlo tree search (MCTS) is a class of online planning algorithms for Markov decision processes (MDPs) and related models that has found success in challenging applications. In the online planning approach, the agent makes a decision in the current state by performing a limited forward search over possible futures...
    Resource Type:
    Dissertation
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    uncertainty. We consider MDPs of the formM = 〈S,A, P,R, γ〉, where S andA are finite sets of states and

  • Learning MDP action models via discrete mixture trees

    Creator:
    Wynkoop, Michael S.
    Abstract:
    This thesis addresses the problem of learning dynamic Bayesian network (DBN) models to support reinforcement learning. It focuses on learning regression tree models of the conditional probability distributions of the DBNs. Existing algorithms presume that the stochasticity in the domain can be modeled as a deterministic function with additive noise....
    Resource Type:
    Masters Thesis
    Full Text:
    significant difference between DMT and the indicated algorithm (p < 0.05; paired t test). TTP DMT-F DMT-S

  • Correct abstraction in counter-planning : a knowledge compilation approach

    Creator:
    Flann, Nicholas S.
    Abstract:
    Knowledge compilation improves search-intensive problem-solvers that are easily specified but inefficient. One promising approach improves efficiency by constructing a database of problem-instance/best-action pairs that replace problem-solving search with efficient lookup. The database is constructed by reverse enumeration- expanding the complete search space backwards, from the terminal problem instances. This approach...
    Resource Type:
    Dissertation
    Full Text:
    compilation approach AN ABSTRACT OF THE THESIS OF Nicholas S. Flann for the degree of Doctor of Philosophy

  • Conceptual Representations within the Social and Material Contexts of an Engineering Workplace and Academic Environments

    Creator:
    Barner, Matthew S.
    Abstract:
    Situated cognition theory emphasizes the role that social and material contexts have on learning and knowledge application. Several studies of engineering workplace environments have noted differences between the social and material contexts of the workplace and those of undergraduate engineering education. No existing research has studied the social and material...
    Resource Type:
    Dissertation
    Full Text:
    or hints for solution[s]” (p. 14) that limit opportunities for students to generate their own

  • Auxiliary Tasks for Efficient Learning of Point-Goal Navigation

    Creator:
    Desai, Saurabh Satish
    Abstract:
    Top-performing approaches to embodied AI tasks like point-goal navigation often rely on training agents via reinforcement learning over tens of millions (or even billions) of experiential steps – learning neural agents that map directly from visual observations to actions. In this work, we question whether these extreme training durations are...
    Resource Type:
    Masters Thesis
    Full Text:
    [18]’s depth prediction task to our setting – significantly altering the architecture to fit the

  • Computational Approaches for RNA Structure Prediction with Dynamic Programming and Deep Neural Networks

    Creator:
    Deng, Dezhong
    Abstract:
    Our goal is to build a system to model the RNA sequences that reveals their structural information by using efficient dynamic programming algorithms and deep learning approaches. We aim to 1) achieve linear-time for RNA secondary structure prediction based on existing minimum free energy models; 2) utilize deep neural networks...
    Resource Type:
    Dissertation
    Full Text:
    deductive system implemented in LinearFold program. Here δE, δM , ξMij , ξ E ij , ξ H ij , ξ S ij, and ω

  • Automated decomposition of complex parts for manufacturing with advanced joining processes

    Creator:
    Massoni, Brandon R.
    Abstract:
    Recent advancements in joining operations and additive manufacturing now allow complex metal parts to be built up from raw materials, as opposed to being machined down from solid blocks. This not only opens up the design space, but also allows for much more efficient manufacturing. By decomposing a complex part...
    Resource Type:
    Dissertation
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    assembly operation. In effect, each volume decomposition operation is the reverse of assembly operation(s

  • Model-based approximation methods for reinforcement learning

    Creator:
    Wang, Xin
    Abstract:
    The thesis focuses on model-based approximation methods for reinforcement learning with large scale applications such as combinatorial optimization problems. First, the thesis proposes two new model-based methods to stablize the value–function approximation for reinforcement learning. The first one is the BFBP algorithm, a batch-like reinforcement learning process which iterates between...
    Resource Type:
    Dissertation
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    learn- ing algorithm. In our approach, we learn the models P (s′|s, a) and R(s′|s, a), and then use

  • Pedestrian distraction : pedestrian behaviors at midblock crossings considering geometric and environmental conditions

    Creator:
    Kautz, Julia Anne
    Abstract:
    Pedestrian distraction at roadway crossings has been correlated with a higher risk of pedestrian-vehicle collisions due to the pedestrian's cognitive, visual, and motor attention being drawn to a wide variety of secondary tasks. This study is different from previous field studies of pedestrian midblock crossings in that the geometric layout...
    Resource Type:
    Masters Thesis
    Full Text:
    : ______________________________________________________ David S. Hurwitz Pedestrian distraction at roadway crossings has been correlated with a

  • Seismic performance of a pile-supported container wharf structures in rockfill

    Creator:
    Kawamata, Yohsuke
    Abstract:
    Recently, the concept of performance based design has become popular for many types of structures, including port facilities under seismic loading. For the case of pile-supported wharves, the level of performance is generally estimated using the displacement capacity of the structure. Therefore, understanding soil-pile interaction is one of the most...
    Resource Type:
    Dissertation
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    stiffness curves (i.e. p-y curves) currently used for design practice. These results were compared with

  • Scale effects on reinforced concrete beams strengthened for shear with discrete externally bonded carbon fiber-reinforced polymer U-wraps

    Creator:
    Dawson, Matthew Ryan
    Abstract:
    Current ACI design provisions for shear in reinforced concrete (RC) beams strengthened with externally bonded carbon fiber-reinforced polymer (CFRP) U-wraps may not adequately account for the effect of scale. This paper describes tests of 6 geometrically scaled beams to identify possible scale effects of such beams. Results indicated that effective...
    Resource Type:
    Masters Thesis
    Full Text:
    ratio (a/d), flexural-tension steel reinforcement ratio (ρs), transverse steel reinforcement ratio (ρv

  • Weakly Supervised Learning for Activity Recognition from Time Series Data

    Creator:
    Guan, Xinze
    Abstract:
    The thesis focuses on activity recognition from sensor data, which has spurred a great deal of interest due to its impact on health care and security. Previous work on activity recognition from multivariate time series data has mainly applied supervised learning techniques which require a high degree of annotation effort...
    Resource Type:
    Dissertation
    Full Text:
    ← {} 2: for each ensemble member m in M do 3: l← SubwindowLength(m), 4: p← {} 5: for each subwindow s of

  • 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:
    distribution. Let the MDP be defined byM = 〈S,A, P,R, γ, P0〉, where S is a finite set of (discrete) states of

  • 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
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    '%#7#+')$#2-99"+-$*)$3'#:P"%97 6$%=-*+!')$3''#+-)"+-$*"90$%-+!)#"##()'3+!"++!' &,)'"#(%')'*+#"%'*$-#'8

  • ThreshKnot: Thresholded ProbKnot for Improved RNA Secondary Structure Prediction

    Creator:
    Zhang, Liang
    Abstract:
    RNA structure prediction is a challenging problem, especially with pseudoknots. Recently, there has been a shift from the classical minimum free energy-based methods (MFE) to partition function-based ones that assemble structures based on base-pairing probabilities. Two typical examples of the latter group are the popular maximum expected accuracy (MEA) method...
    Resource Type:
    Masters Thesis
    Full Text:
    3000 # b a s e p a ir s w h o s e p ro b . > θ sequence length θ = 0: ~n 2.0 θ = 0.01

  • Heuristic search in symbolic probability inference

    Creator:
    Pan, Yonghong
    Abstract:
    I present a new heuristic search approach to compute approximate answers for the probability query in belief nets. This approach can compute the 'best' bounds for a query in a period of any given time (if time permitted, it will get an exact value). It inherits the essence of Symbolic...
    Resource Type:
    Capstone Project
    Full Text:
    of the example sum-over: C 4 P(AIS,C) P(AIS) S C A=0 A=l (0, 0) 0.8 0.2 (0, 1) 0.5 0.5

  • High-speed implementation of the RSA cryptosystem

    Creator:
    Peng, Yanqun
    Abstract:
    A public key cryptosystem allows two or more parties to securely communicate over an insecure channel without establishing a physically secure channel for key exchange. The RSA cryptosystem is the most popular public key cryptosystem ever invented. It is based on the difficulty of factoring large composite numbers. Once the...
    Resource Type:
    Masters Thesis
    Full Text:
    the two primes. To generate the two keys, choose two distinct large prime numbers, p and q. Compute

  • 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

  • A study on student perceptions of principles of logic and their application to the principle of mathematical induction

    Creator:
    Boone, Allan R.
    Abstract:
    The purpose of this article is to explore student reasoning with regard to problems in logic, particularly those related to the Principle of Mathematical Induction (PMI). The five case studies presented build off of work done by other researchers, most notably Dubinsky and Harel, who both looked at how students'...
    Resource Type:
    Masters Thesis
    Full Text:
    ). In any case, showing P(1) or 1 ∈ 𝑆 is called the base case and showing that for all natural

  • Improving automated email tagging with implicit feedback

    Creator:
    Sorower, Mohammad Shahed
    Abstract:
    Machine learning systems are generally trained offline using ground truth data that has been labeled by experts. However, these batch training methods are not a good fit for many applications, especially in the cases where complete ground truth data is not available for offline training. In addition, batch methods do...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Mohammad S. Sorower

  • A Benchmarking Study of Unsupervised Anomaly Detection Algorithms

    Creator:
    Emmott, Andrew F.
    Abstract:
    It is common practice in the unsupervised anomaly detection literature to create experimental benchmarks by sampling from existing supervised learning datasets. We seek to improve this practice by identifying four dimensions important to real-world anomaly detection applications --- point difficulty, clusteredness of anomalies, relevance of features, and relative frequency of...
    Resource Type:
    Masters Thesis
    Full Text:
    Table Page 6.1 Benchmark Acceptance Rate by Metric and p-value . . . . . . . . . 46 6.2 Benchmark

  • Optimal inference with local expressions

    Creator:
    Borujerdi, Mohammad
    Abstract:
    Probabilistic inference using Bayesian networks is now a well-established approach for reasoning under uncertainty. Among many e ciency-driven tech- niques which have been developed, the Optimal Factoring Problem (OFP) is distinguished for presenting a combinatorial optimization point of view on the problem. The contribution of this thesis is to extend...
    Resource Type:
    Dissertation
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    where T =/�X S, X � dim(S), and for every t 2 T , let St = fs : 8v 2 dim(T ); s(v) = t(v)g. Then gt = P

  • Learning with Partial Supervision for Clustering and Classification

    Creator:
    Pei, Yuanli
    Abstract:
    In the field of machine learning, clustering and classification are two fundamental tasks. Traditionally, clustering is an unsupervised method, where no supervision about the data is available for learning; classification is a supervised task, where fully-labeled data are collected for training a classifier. In some scenarios, however, we may not...
    Resource Type:
    Dissertation
    Full Text:
    0.75 0.8 α C la s s P u ri ty HJA Birdsong CSP SP 0 0.2 0.4 0.6 0.8 1 0.4 0.45 0.5

  • Variational Satisfiability Solving

    Creator:
    Young, Jeffrey M.
    Abstract:
    Over the last two decades, satisfiability and satisfiability-modulo theory (SAT/SMT) solvers have grown powerful enough to be general purpose reasoning engines throughout software engineering and computer science. However, most practical use cases of SAT/SMT solvers require not just solving a single SAT/SMT problem, but solving sets of related SAT/SMT problems....
    Resource Type:
    Dissertation
    Full Text:
    example, A〈p, q〉 ∧ B〈r, s〉 has four variants, while A〈p, q〉 ∧ A〈r, s〉 has only two (p ∧ r and q ∧ s). It

  • Learning greedy policies for the easy-first framework

    Creator:
    Xie, Jun
    Abstract:
    Easy-first, a search-based structured prediction approach, has been applied to many NLP tasks including dependency parsing and coreference resolution. This approach employs a learned greedy policy (action scoring function) to make easy decisions first, which constrains the remaining decisions and makes them easier. This thesis studies the problem of learning...
    Resource Type:
    Masters Thesis
    Full Text:
    state function, and A(s) is a function that gives the set of allowed actions from a given state. Given

  • Approximation Schemes in Planar Graphs

    Creator:
    Zheng, Baigong
    Abstract:
    There are growing interests in designing polynomial-time approximation schemes (PTAS) for optimization problems in planar graphs. Many NP-hard problems are shown to admit PTAS in planar graphs in the last decade, including Steiner tree, Steiner forest, two- edge-connected subgraphs and so on. We follow this research line and study several...
    Resource Type:
    Dissertation
    Full Text:
    solution OPT (G). Since S is the union of optimal solutions on each piece, we know that |S| ≥ |OPT (G) \ P

  • Sliding-mode control of the super maneuverable aircraft

    Creator:
    Koo, Chang Sul
    Abstract:
    In this thesis, A nonlinear methodology for the control of the highly maneuverable, high performance aircraft HARV (F-18) is studied by using sliding-mode control (SMC). This control law, which takes a continuous function when the input constraints are not considered, satisfies the reachability condition by which concerned states are driven...
    Resource Type:
    Dissertation
    Full Text:
    vector f ° at a point p on the sliding surface s(x) = 0, a tangential vector f° perpendicular to the

  • Machine learning for improving the quality of citizen science data

    Creator:
    Yu, Jun
    Abstract:
    Citizen Science is a paradigm in which volunteers from the general public participate in scientific studies, often by performing data collection. This paradigm is especially useful if the scope of the study is too broad to be performed by a limited number of trained scientists. Although citizen scientists can contribute...
    Resource Type:
    Dissertation
    Full Text:
    - based AUC are computed over S species. . . . . . . . . . . . . . . . . . . . 89 7.3 Difference in

  • Bayesian optimization with empirical constraints

    Creator:
    Azimi, Javad
    Abstract:
    Bayesian Optimization (BO) methods are often used to optimize an unknown function f(•) that is costly to evaluate. They typically work in an iterative manner. In each iteration, given a set of observation points, BO algorithms select k ≥ 1 points to be evaluated. The results of those points are...
    Resource Type:
    Dissertation
    Full Text:
    for computing a p-safe uniform schedule with maximum number of stages given the scheduling

  • Update programming -- a safe approach to software maintenance

    Creator:
    Ren, Deling
    Abstract:
    Software maintenance accounts for a large portion of the software development cost, particularly the process of updating programs either to adapt for requirement change or to enhance design or efficiency. Currently, program updates are generally performed manually by programmers using text editors. This is an unreliable method because syntax and...
    Resource Type:
    Dissertation
    Full Text:
    ˜ � “�“�›/œ‚–X¦Z§¨—žœ � œb¥t—�©y–b›/˜Œª«–X¡¢‚—w˜P¢�–b¢�¦i˜ oHG #%$'&)()*,+�-.$/* Q¬#%…SO;O,sa-�]vQC]^…S­

  • A Study of Temporal Convolutional Neural Networks for Music Language Modeling as Applied to Automatic Music Transcription

    Creator:
    Meyn, Matthew
    Abstract:
    Automatic music transcription (AMT) is the task, given an acoustic representation of music, to recover a symbolic notation of the written notes expressed by the sound. Transcribing music with multiple notes sounding simultaneously is difficult for both humans and machines. Much existing work on AMT has focused on suitable acoustic...
    Resource Type:
    Capstone Project
    Full Text:
    -dilated discrete convolution with kernel k is defined as (F ∗l k)(p) = Σs+lt=pF (s)k(t) Dilated

  • Metacontent based techniques for the regression testing of component based software : a case study

    Creator:
    Chattopadhyay, Soumya
    Abstract:
    Component based software technologies are viewed as essential for creating the software systems of the future. However the use of externally provided components has serious drawbacks for a wide range of software engineering activities often because of a lack of information about the components. One such drawback involves validation of...
    Resource Type:
    Capstone Project
    Full Text:
    / ~ T, a set of test cases to execute on P /. 2. Test P/ with T~ establishing P/'s correctness with

  • Modeling and dynamics analysis of P2P networks based on evolutionary games

    Creator:
    Cho, Seungyun
    Abstract:
    Since free riders in P2P network reduce the system's performance, how to maintain and encourage the nodes' cooperation is an important aspect of P2P related research. In this thesis, a P2P system is modeled based on two games: stag hunt game and snowdrift game. To relate the model to the...
    Resource Type:
    Masters Thesis
    Full Text:
    ......................................................................................................... 22 TABLE OF CONTENTS(Continued) Page 4.5.1 R>T, and S>P

  • Protein secondary structure prediction using conditional random fields and profiles

    Creator:
    Shen, Rongkun
    Abstract:
    Protein secondary structure prediction plays a pivotal role in predicting protein folding in three-dimensions. Its task is to assign each residue one of the three secondary structure classes helix, strand, or random coil. This is an instance of the problem of sequential supervised learning in machine learning. This thesis describes...
    Resource Type:
    Masters Thesis
    Full Text:
    observations X and states Y , ( , )P X Y and make predictions to compute the conditional distribution ( )P

  • Metacontent based techniques for the regression testing of component based software : a case study

    Creator:
    Williams, Vasanth
    Abstract:
    Component based software technologies are viewed as essential for creating the software systems of the future. However, the use of externally provided component has serious drawbacks for a wide range of software engineering activities often because of a lack of information about the components. One such drawback involves validation of...
    Resource Type:
    Capstone Project
    Full Text:
    proceeds as follows: 1. Select T/ s T, a set of test cases to execute on P /. 2. Test P / with T

  • Resource placement, data rearrangement, and Hamiltonian cycles in torus networks

    Creator:
    Bae, Myung Mun
    Abstract:
    Many parallel machines, both commercial and experimental, have been/are being designed with toroidal interconnection networks. For a given number of nodes, the torus has a relatively larger diameter, but better cost/performance tradeoffs, such as higher channel bandwidth, and lower node degree, when compared to the hypercube. Thus, the torus is...
    Resource Type:
    Dissertation
    Full Text:
    Member (Timothy A. Budd) Committee Member (Prasad Tadepalli) uate School Representative (John P

  • Reinforcement learning for job-shop scheduling

    Creator:
    Zhang, Wei, 1960-
    Resource Type:
    Dissertation
    Full Text:
    Methods vs. AI Methods Starting in the 1950's operations researchers began advocating formal optimization

  • Nonuniform Sampling Of Band-limited Functions

    Creator:
    Al-Hammali, Hussain Y.
    Abstract:
    In this thesis, we will study certain generalizations of the classical Shannon Sampling Theorem, which allows for the reconstruction of a pi-band-limited, square-integrable function from its samples on the integers. J. R. Higgins provided a generalization where the integers can be perturbed by less than 1/4, which includes nonuniform and...
    Resource Type:
    Dissertation
    Full Text:
    formula (1.3) for more general choices of the � k ’s and for f in more general function spaces. In