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  • Graph Imitation Learning for Optimal Joint Beamforming and Antenna Selection

    Creator:
    Shrestha, Sagar
    Abstract:
    Transmit beamforming is an important technique employed to improve efficiency and signal quality in wireless communication systems by steering signals towards their in- tended users. It often arises jointly with the antenna selection problem due to various reasons, such as limited number of radio frequency (RF) chains and energy/resource effi-...
    Resource Type:
    Masters Thesis
    Full Text:
    Imitation Learning For Optimal Joint Beamforming and Antenna Selection Abstract approved: Xiao Fu

  • 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:
    : Xiao Fu We consider the problem of computing the cannonical polyadic decomposition (CPD) for large

  • Object Tracking-by-Segmentation in Videos

    Creator:
    Chen, Sheng
    Abstract:
    This thesis focuses on the problem of object tracking. Given a video, the general objective of tracking is to track the location over time of one or more targets in the image sequence. This is a very challenging task as algorithms need to deal with problems such as appearance variations,...
    Resource Type:
    Dissertation
    Full Text:
    thesis.dvi AN ABSTRACT OF THE THESIS OF Sheng Chen for the

  • Stochastic and Numerical Analysis for Optimization Problems

    Creator:
    Jiang, Huanqun
    Abstract:
    There are three chapters of manuscripts in this dissertation and all of them are talking about a specific theme: stochastic control, but with completely different perspectives. In the first manuscript, we solve the optimal barrier strategy for dividend distribution in a complicated Lévy system. In this system, the capital of...
    Resource Type:
    Dissertation
    Full Text:
    classes, Professor Chen Yong on his suggestion for the economic modeling. Last but not the least, I like

  • Data-Driven Approaches For Decoding Volitional Movement Intent From Bioelectrical Signals

    Creator:
    Cunha Dantas, Henrique
    Abstract:
    There are nearly two million limb amputees living in the United States of America. Loss of limbs results in profound changes in one's life. However, the underlying neural circuitry and much of the ability to sense and control movements of their missing limb is retained even after limb loss. This...
    Resource Type:
    Dissertation
    Full Text:
    committee: Prof. Alan Fern, Prof. Xiao Fu, Prof. Fuxin Li, and Prof. Julie Tucker for their insightful

  • Action Segmentation in Videos: Deep Models, Prediction Diffusion, and Deep-Temporal Augmentations

    Creator:
    Aziere, Nicolas
    Abstract:
    This paper addresses the high model complexity and overconfident frame labeling of state-of-the-art (SOTA) action segmenters. Their complexity is typically justified by the need to sequentially refine action segmentation through multiple stages of a deep architecture. However, this multistage refinement does not take into account uncertainty of frame labeling predicted...
    Resource Type:
    Dissertation

  • Regularization-Based Data Integration and Its Application to Genome-Wide Association Studies

    Creator:
    Li, Kai
    Abstract:
    In genome-wide association studies, it is often challenging to have consistent findings from independent studies. This "lack of reproducibility" issue is partially caused by the relatively small sample size compared to the number of genetic markers in every single study. Therefore, researchers have developed statistical methods to integrate multiple studies...
    Resource Type:
    Dissertation
    Full Text:
    Zhang, Hanzhong Xu, Meng Meng and Han Mei for their support. My gratitude also goes to all the people

  • Pixel- and Frame-level Video Labeling using Spatial and Temporal Convolutional Networks

    Creator:
    Lei, Peng
    Abstract:
    This dissertation addresses the problem of video labeling at both the frame and pixel levels using deep learning. For pixel-level video labeling, we have studied two problems: i) Spatiotemporal video segmentation and ii) Boundary detection and boundary flow estimation. For the problem of spatiotemporal video segmentation, we have developed recurrent...
    Resource Type:
    Dissertation
    Full Text:
    University: Mohamed Amer, Sheng Chen, Liping Liu, Jun Li, Anirban Roy, Behrooz Mahasseni, Michael Lam

  • Topological Learning for Robotic Exploration and Navigation in Uncertain Environments

    Creator:
    Saroya, Manish R.
    Abstract:
    The effectiveness of robot autonomy is governed by the ability to make decisions based on online sensor measurements and a prior belief of the environment. Uncertainty in the environment introduces challenges to robotic decision making. This thesis address two key robot decision making problems: exploration and navigation. The robotic exploration...
    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:
    , Anirban Roy, Michael Lam, Sheng Chen, Peng Lei, Christos Margiolas, Alberto Garcia, Suren Jayasuriya and