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Filtering by: Creator Duringer, J. M. Remove constraint Creator: Duringer, J. M. Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad Committee Member Wong, Weng-Keen Remove constraint Committee Member: Wong, Weng-Keen

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  • 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

  • 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

  • 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:
    , t,K) = N,M∑ i,j (θ1pi,j + θ2tj + θ3Ki,1 + ...+ θ2+kKi,k)xi,j Let opponent capacity Cj be the

  • Interpretable Machine Learning: Applications in Biology and Genomics

    Creator:
    Danaee, Padideh
    Abstract:
    Machine learning (ML) and deep learning (DL) models impact our daily lives with applications in natural language modeling, image analysis, healthcare, genomics, and bioinformatics. The exponential growth of biological sequence data necessitates accompanying advances in computational methods. Although deep learning is highly effective for detecting and classifying biological sequences, challenges...
    Resource Type:
    Dissertation
    Full Text:
    that has base pair (i, j) with all other base pairs such that i < i0 < j0 < j as with (i0, j0), or i

  • A SAT-based planning framework for optimizing resource production

    Creator:
    Ventura, Christopher
    Abstract:
    Domain-independent automated planning is concerned with computing a sequence of actions that can transform an initial state into a desired goal state. Resource production domains form an interesting class of such problems, in that they typically require reasoning about concurrent durative-actions with continuous effects while minimizing some cost function. Although...
    Resource Type:
    Masters Thesis
    Full Text:
    ‘Continue(A)[i,j]’ to represent the fact that durative action ‘A’ is continuing at significant time point

  • Active learning of constraints for semi-supervised clustering

    Creator:
    Xiong, Sicheng
    Abstract:
    Semi-supervised clustering aims to improve clustering performance by considering user supervision in the form of pairwise constraints. In this paper, we study the active learning problem of selecting pairwise must-link and cannot-link constraints for semisupervised clustering. We consider active learning in an iterative manner where in each iteration queries are...
    Resource Type:
    Masters Thesis
    Full Text:
    neighborhood probability. Given the similarity matrix M generated by previous steps, let M(xi,xj) denote the

  • 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
    Full Text:
    Environments (MCE). We use ‘m’ to indicate the activate mode/action required in that state. Given M = 4 , we

  • 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:
    each round the starting position 21 T a b le 3. 1: M M re su lt s fo r co n tr ol ta sk s

  • UCT for tactical assault battles in real-time strategy games

    Creator:
    Balla, Radha-Krishna
    Abstract:
    We consider the problem of tactical assault planning in real-time strategy games where a team of friendly agents must launch an assault on an enemy. This problem offers many challenges including a highly dynamic and uncertain environment, multiple agents, durative actions, numeric attributes, and different optimization objectives. While the dynamics...
    Resource Type:
    Masters Thesis
    Full Text:
    friendly groups and m enemy groups, the number of action choices would be, 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓