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Filtering by: Creator Brooks, J. R. Remove constraint Creator: Brooks, J. R. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad

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  • 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:
    (�%������������������������ A6 ��)IF&�+'#2�!�'#,�%��H2'��'"�!&(�%����������������������� A6 ��)�J'!!:�"���#(%���#�#��++���+42

  • 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
    Full Text:
    - tical performance at the p = 0.05 level. This plot was produced by the R package scmamp [Calvo and

  • Analytical Methods for Improving Causal Inference

    Creator:
    Sinha, Meghamala
    Abstract:
    Causal inference is an important analytical tool to bridge the gap between prediction and decision-making. However, learning a causal network solely from data is a challenging task. In this work, various techniques have been explored for a better and improved causal network learning from data. Firstly, the problem of learning...
    Resource Type:
    Dissertation
    Full Text:
    distribution of p after intervention is: p(V1, ..., Vn) = ∏ Vi∈Oe pi(Vi | Pa(Vi)) · ∏ Vj∈Ie p′j(Vj | Pa(Vj

  • 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
    Full Text:
    learn- ing algorithm. In our approach, we learn the models P (s′|s, a) and R(s′|s, a), and then use

  • Visual object discovery and understanding

    Creator:
    Yuan, Jialin
    Abstract:
    Learning to recognize objects is a fundamental and essential step in human perception and understanding of the world. Accordingly, research of object discovery across diverse modalities plays a pivotal role in the context of computer vision. This field not only contributes significantly to enhancing our understanding of visual information but...
    Resource Type:
    Dissertation
    Full Text:
    almost as good as mask R-CNN without depending on a two-stage framework. Note that the training of the

  • Designing and understanding information retrieval systems using collaborative filtering in an academic library environment

    Creator:
    Jung, Seikyung
    Abstract:
    Accessing information on the Web has become ingrained into our daily lives, and we seek information from many different sources, including conference and journal publications, personal web pages, and others. Increasingly, web-based information retrieval systems such as web-based search engines, library on-line catalog systems, and subscription-based federated search systems are...
    Resource Type:
    Dissertation

  • Test case prioritization

    Creator:
    Malishevsky, Alexey Grigorievich
    Abstract:
    Regression testing is an expensive software engineering activity intended to provide confidence that modifications to a software system have not introduced faults. Test case prioritization techniques help to reduce regression testing cost by ordering test cases in a way that better achieves testing objectives. In this thesis, we are interested...
    Resource Type:
    Dissertation
    Full Text:
    domain (set of allowable inputs) of P, and R be the range (set of program outputs given inputs from D

  • 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:
    . Correlation between each pair of axes:∑T i=1(si−µs)(vi−µv)√∑T i=1(si−µs) ∑T j=1(vj−µv) . O(N) Table 2.1

  • 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

  • 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:
    . J. Becka, M. Biesiada, M. J. Boniecki, J. M. Bujnicki, S.-J. Chen, C. Y. Cheng, F.-C. Chou, A. R