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Filtering by: Creator Le Roy, Frédéric Remove constraint Creator: Le Roy, Frédéric Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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  • Structural Results and Approximation Algorithms in Minor-free Graphs

    Creator:
    Le, Hung V.
    Abstract:
    Planarity has been successfully exploited to design faster and more accurate approximation algorithms for many graph optimization problems. The celebrated theorem of Kuratowski completely characterizes planar graphs as those excluding K_5 and K_{3,3} as minors. Kuratowski's theorem allows one to generalize planar graphs to H-minor-free graphs: those that exclude a...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Hung Le for the

  • Analysis and Design of Low Voltage LC Oscillators and their Application to Wireless Sensor Networks

    Creator:
    Guha Roy, Ankur
    Abstract:
    This dissertation focuses on the analysis, design, and application of inductor-capacitor (LC) oscillators for wireless sensor networks (WSNs). First an analysis and design optimization approach for enhanced swing, low power CMOS LC oscillators is presented. A phasor based analysis is used for determining the amplitude and phase noise of these...
    Resource Type:
    Dissertation
    Full Text:
    Application to Wireless Sensor Networks AN ABSTRACT OF THE DISSERTATION OFAnkur Guha Roy for the degree of

  • A study of methods for fine-grained object classification of arthropod specimens

    Creator:
    Lin, Junyuan
    Abstract:
    Object categorization is one of the fundamental topics in computer vision research. Most current work in object categorization aims to discriminate among generic object classes with gross differences. However, many applications require much finer distinctions. This thesis focuses on the design, evaluation and analysis of learning algorithms for fine- grained...
    Resource Type:
    Masters Thesis

  • Understanding Software-2.0: A Study of Machine Learning library usage and evolution

    Creator:
    Dilhara, Malinda, Ketkar, Ameya, and Dig, Danny
    Abstract:
    Enabled by a rich ecosystem of Machine Learning (ML) libraries, programming using learned models, i.e., Software-2.0, has gained substantial adoption. However, we do not know what challenges developers encounter when they use ML libraries. With this knowledge gap, researchers miss opportunities to contribute to new research directions, tool builders do...
    Resource Type:
    Research Paper
    Full Text:
    engineering Model Training Model evaluation Model Deployment Occurrences Scenario sk le ar n ke ra s to

  • 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

  • Exploration of regression models for cancer noncoding mutation recurrence

    Creator:
    Xu, Tanjin
    Abstract:
    An important impact of the genome technology revolution will be the elucidation of mechanisms of cancer pathogenesis, leading to improvements in the diagnosis of cancer and the selection of cancer treatment. Integrated with current well-studied massive knowledge and findings about the role of protein-coding mutations in cancer, demystifying the functional...
    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

  • Machine Learning for Precision Medicine: Application to Cancer Chemotherapy Response Prediction and Wound Healing Status Assessment

    Creator:
    Wei, Qi
    Abstract:
    Ph.D. candidate Qi Wei's thesis consists of two projects: Chemotherapy Project: a study based on the research paper "Predicting chemotherapy response of various cancer types using a variational auto-encoder approach" submitted to the bioRxiv preprint archive and accepted by the BMC bioinformatics; and Wound Monitor Project: implementing and assessing analytics...
    Resource Type:
    Dissertation

  • Deep Convolutional Network on Point Clouds for 3D Scene Understanding

    Creator:
    Wu, Wenxuan
    Abstract:
    As one of the most popular data types, the point cloud is widely used in various appli- cations, including computer vision, computer graphics and robotics. The capability to directly measure 3D point clouds is invaluable in those applications as depth information could remove a lot of the segmentation ambiguities in...
    Resource Type:
    Dissertation

  • 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