Search Constraints

Start Over
Filtering by: Creator Brett, M. Remove constraint Creator: Brett, M. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science Committee Member Li, Fuxin Remove constraint Committee Member: Li, Fuxin

Search Results

  • 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:
    generative methods: nearest neighbors. We run our pre-trained agent for 1 million game steps, M , with

  • Machine Learning Methods for the Discovery and Analysis of MicroRNAs

    Creator:
    Bell, Jimmy D.
    Abstract:
    MicroRNAs are a highly conserved class of small endogenous RNA, about ~22nt in length, involved in post-transcriptional gene silencing and have prominent roles in disease and development. Though the process of microRNA discovery was once an arduous task, the advent of high throughput sequencing technology has resulted in novel microRNAs...
    Resource Type:
    Masters Thesis

  • Robust and Efficient Classification of Videos in the Wild

    Creator:
    Mahasseni, Behrooz
    Abstract:
    Recognizing human actions in videos is a long-standing problem in computer vision with a wide range of applications including video surveillance, content retrieval, and sports analysis. This thesis focuses on addressing efficiency and robustness of video classification in unconstrained real-world settings. The thesis work can be broadly divided into four...
    Resource Type:
    Dissertation
    Full Text:
    the action class; and h denotes the space-time locations of the win- dows in A. For a set of M action

  • An analysis of training methodologies for deep visual trackers

    Creator:
    Fiez, Trevor
    Abstract:
    This thesis considers the problem of training convolutional neural networks for online visual tracking. A major challenge for single object visual tracking is that most training sets with frame-level track annotations are quite small, due to the prohibitive cost of manual annotation. Current training approaches either supplement the annotations with...
    Resource Type:
    Masters Thesis

  • Large Scale Tensor Decomposition Algorithms Using Block-randomized Stochastic Proximal Gradient

    Creator:
    Gao, Cheng
    Abstract:
    We consider the problem of computing the cannonical polyadic decomposition (CPD) for large-scale dense tensors. This work is a combination of alternating least squares and fiber sampling. Data sparsity can be leveraged to handle large tensor CPD, but this route is not feasible for dense data. Inspired by stochastic optimization's...
    Resource Type:
    Masters Thesis
    Full Text:
    0 100 200 300 400 no. of MTTKRP computed 10-6 10-4 10-2 100 M S E BrasCPD ( = 1.5) AdaCPD