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Events for May 02, 2022

  • Phd Defense - Bowen Zhang

    Mon, May 02, 2022 @ 09:00 AM - 10:30 AM

    Computer Science

    University Calendar

    PhD Candidate: Bowen Zhang

    Committee chair: Prof. Leana Golubchik (CS dept.), Prof. Fei Sha,
    Committee members: Prof. Laurent Itti (CS dept.), Prof. Shri Narayanan (EE dept.)

    May. 2 Monday 9:00am-10:30am

    Title: Visual Representation Learning with Structural Prior

    Abstract: Visual representation learning is crucial for building a robust and effective visual understanding system. The goal is to build general-purpose representations to benefit multiple downstream tasks (\ie image/video classification, segmentation, retrieval, etc.) With the accessibility to large-scale datasets and the advance in complex learning methods, sophisticated neural architectures and novel training approaches have been proposed to improve visual representation. However, obtaining a versatile representation is still yet an open question. This thesis aims to leverage the visual structure to obtain more general visual representations. The key observation is that the visual components (\ie images and videos) contain structure. It can be decomposed into atomic components such as objects, attributes, clips, etc. For example, images can be decomposed into objects and can be further described by attributes. Similarly, videos can describe complex scenes composed of multiple clips or shots, where each depicts a semantically coherent event or action. As atomic components are shareable across modalities and tasks, we hope the hierarchical visual representation that is compiled from the atomic representation could achieve better generalization ability. In this thesis, we studied two scenarios to obtain the visual structures: the structure from parallel visual and text data and the pure visual domain. We achieved state-of-the-art performance on video and text retrieval, moment localization in a video corpus, image and text retrieval, action recognition, and visual storytelling with the proposed hierarchically visual representation.

    WebCast Link: https://usc.zoom.us/j/92058237989

    Audiences: Everyone Is Invited

    Contact: Lizsl De Leon

  • PhD Thesis Proposal - Jason Gregory

    Mon, May 02, 2022 @ 01:00 PM - 03:00 PM

    Computer Science

    University Calendar

    PhD Thesis Proposal - Jason Gregory

    Title: Decision Support Systems for Adaptive Experimental Design in Field Robotics

    Field robots - agents that operate in complex, natural settings - have the potential for making major, tangible impact to human-robot teaming, but also face the toughest of challenges because the physical world is an unforgiving place. Experimentation plays an integral role in the research and development of fieldable systems and this must be performed in representative conditions that leverage human supervision to effectively understand capabilities of the system, assess individual components and their interactions, manage risk, and interpret results. Adaptive decision making led by a human is required for the construction of experiments, referred to as experimental design, to use insights gained from previous experiments and overcome the inherent complexity of autonomous field robotic systems and operational environments. Human experimenters, however, inherently have several shortcomings, including an inability to reason over large-scale data, sub-optimal uncertainty estimation, and biased decision making. These shortcomings can produce disastrous outcomes, including the selection of low-value experiments that introduce unnecessary delays in building system understanding as well as the selection of risky experiments that can result in major equipment damage or physical injury. To mitigate the human's drawbacks while boosting their indispensable skill sets, we seek to develop decision support systems (DSS) that can assist an experimenter during the decision making process of experiment design and reduce experimental costs by constructing more informative experiments. In this talk, I will present recent efforts in human-in-the-loop decision making for adaptive experimental design, specifically in the context of field robotics, through the development of applicable DSSs.

    Satyandra K. Gupta (advisor, Aerospace and Mechanical Engineering, Computer Science)
    Gaurav Sukhatme (Computer Science)
    Heather Culbertson (Computer Science)
    Stefanos Nikolaidis (Computer Science)
    Quan Nguyen (Aerospace and Mechanical Engineering, Computer Science)

    Location: https://usc.zoom.us/j/2562545595?pwd=RnJUdWNTaStveEdQSUFiSjhkL2o5Zz09

    Date: Monday, May 2, 2022 at 1-3PM.

    WebCast Link: https://usc.zoom.us/j/2562545595?pwd=RnJUdWNTaStveEdQSUFiSjhkL2o5Zz09

    Audiences: Everyone Is Invited

    Contact: Lizsl De Leon