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Filtering by: Creator Noga, Edward J. Remove constraint Creator: Noga, Edward J. Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad

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  • 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

  • The density signature

    Creator:
    Migler-VonDollen, Theresa
    Abstract:
    In real networks, identifying dense regions is of great importance. For example, in a network that represents academic collaboration, authors within the densest component of the graph tend to be the most prolific. Dense subgraphs often identify communities in social networks. And dense subgraphs can be used to discover regulatory...
    Resource Type:
    Dissertation
    Full Text:
    GF C J L I N M D H E A B K GF C J L I N M D H E A B K GF C J L I N M D H E

  • 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

  • Selling and buying in a distributed virtual market place

    Creator:
    Bella, Ravi
    Abstract:
    We present a model for a distributed virtual market place that can be con­structed on the Internet to support selling and buying requests, such as those found as classified advertisements. One requirement for a transaction to take place in the virtual market place is that a sell request and a...
    Resource Type:
    Capstone Project
    Full Text:
    from AREAS start with Area= B.Scope 8 J OR connect by prior AreaNo = Parent;) B.Loc IN

  • 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:
    . Google street view: Capturing the world at street level. IEEE Computer, 43:32–38, 06 2010. [3] J. Deng

  • Investigating Latent State and Uncertainty Representations in Reinforcement Learning

    Creator:
    Koul, Anurag
    Abstract:
    Learning latent space representations of high-dimensional world states has been at the core of recent rapid growth in reinforcement learning(RL). At the same time, RL algo- rithms have suffered from ignored uncertainties in the predicted estimates of model-free or model-based methods. In our work, we investigate both of these aspects...
    Resource Type:
    Dissertation

  • Leveraging Structures of the Data in Deep Learning

    Creator:
    Li, Xingyi
    Abstract:
    The performance of deep learning frameworks could be significantly improved through considering the particular underlying structures for each dataset. In this thesis, I summarize our three work about boosting the performance of deep learning models through leveraging structures of the data. In the first work, we theoretically justify that, for...
    Resource Type:
    Dissertation
    Full Text:
    ‖1 ≤ 1, ‖wi‖1 ≤ B } . (2.2) For any x1, . . . ,xN ∈ Rd, we have ĜN (F ) ≤ cLB(ln d)1/2 N max j,j

  • 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:
    captured by: J(Q) = E(x1,···,x|Q|) [ E(y1,···,y|Q|) [ max { y1, . . . , y|Q| } ∣∣∣D, (x1, · · ·, x|Q

  • Structured learning with latent variables : theory and algorithms

    Creator:
    Zhao, Kai
    Abstract:
    Most tasks in natural language processing (NLP) try to map structured input (e.g., sentence or word sequence) to some form of structured output (tag sequence, parse tree, semantic graph, translated/paraphrased/compressed sentence), a problem known as “structured prediction”. While various learning algorithms such as the perceptron, maximum entropy, and expectation-maximization have...
    Resource Type:
    Dissertation
    Full Text:
    +2 . . . yi) = max y1,...,yi−k i∑ j=1 fw(yj ;x, yj−k+1 . . . yj−1) = max yi−k+1 Gw(x, yi−k+1

  • Stake-Free Evaluations of Black-Box Optimization and Spatio-Temporal Graph Network Algorithms

    Creator:
    Merrill, Erich, III
    Abstract:
    Papers proposing novel machine learning algorithms tend to present the algorithm or technique in question in the best possible light. The standard practice is generally for authors to emphasize their proposed algorithms' performance in the precise setting where it is maximally impressive, often by only fully evaluating their best known...
    Resource Type:
    Dissertation
    Full Text:
    (n)) do 9: (h, i) =arg maxxh,j∈Lh g(xh,j), where Lh contains all leaves of τ at depth h 10: if g(xh