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Filtering by: Creator He, Feng Remove constraint Creator: He, Feng Committee Member Li, Fuxin Remove constraint Committee Member: Li, Fuxin

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  • Characterizing On-Chip Traffic Patterns in Throughput Processors: A Deep Learning Approach

    Creator:
    Ramamurthy, Abhishek
    Abstract:
    The machine learning and deep learning models have been very lightly explored in analyzing the behavior of On-Chip network traffic. These models have proven their potential in pattern recognition, classification etc... In this paper we analyze the spatial pattern that each workload exhibits in its life cycle during execution. We...
    Resource Type:
    Masters Thesis
    Full Text:
    guidance when I had any question related to research or writing. He consistently allowed this paper to be

  • Ideal Thumbnail-Preserving Encryption for Balancing Image Privacy and Usability

    Creator:
    Tajik, Kimia
    Abstract:
    In this dissertation, we propose Ideal Thumbnail-Preserving Encryption (Ideal TPE), as a special case of format-preserving encryption, to balance image privacy and usability concerns in a cloud environment. We first introduce a concrete construction for Ideal TPE, that provably leaks nothing about the plaintext (unencrypted) image beyond its thumbnail. We...
    Resource Type:
    Dissertation

  • 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
    Full Text:
    profoundly grateful for your presence in my life. I extend my deepest thanks to my colleagues, Liqiang He

  • 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

  • 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:
    to answer my questions and giving me useful advice to overcome challenges. He also provided

  • Anomaly Detection and Probabilistic Diagnosis for Automated Data Quality Control

    Creator:
    Zemicheal, Tadesse H.
    Abstract:
    Advances in sensor technology are greatly expanding the range of quantities that can be measured while simultaneously reducing the cost. However, deployed sensors drift out of calibration and fail, so every sensor network requires quality control procedures to promptly detect these failures. To address these problems, we propose a two-level...
    Resource Type:
    Dissertation
    Full Text:
    , writing and presentation. I am very grateful, for the opportunities that he gave me to travel, and attend

  • Part-based and Uncertainty-Aware Few-shot Object Segmentation in Images

    Creator:
    Nguyen, Khoi D.
    Abstract:
    This dissertation addresses few-shot object segmentation in images. The goal of segmentation is to label every image pixel with a class of the object occupying that pixel, where the class may represent a semantic object category or instance. In few-shot segmentation, training and test datasets have different classes. Every new...
    Resource Type:
    Dissertation
    Full Text:
    me through my Ph.D. at Oregon State University. He has been encouraging, supportive and patient

  • 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:
    . He has been encouraging, supportive and patient throughout my graduate study. I learned a lot from

  • 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

  • Semantic image segmentation using domain constraints

    Creator:
    Roy, Anirban
    Abstract:
    This dissertation addresses the problem of semantic labeling of image pixels. In the course of our work, we considered different types of semantic labels, including object classes (e.g., car, person), 3D depth values (in the range 0 to 80 meters), and affordance classes (e.g., walkable, sittable). Semantic pixel labeling is...
    Resource Type:
    Dissertation