Index Catalog // ScholarsArchive@OSU

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

On Avoiding Power-Seeking by Artificial Intelligence

Creator:: Turner, Alexander M.
Abstract:: We do not know how to align a very intelligent AI agent's behavior with human interests. I investigate whether—absent a full solution to this AI alignment problem—we can build smart {\ai} agents which have limited impact on the world, and which do not autonomously seek power. In this thesis, I...
Resource Type:: Dissertation

A Framework for Evaluating the Comprehensiveness of Continuous Improvement in Academic Computing Programs. A 360-Degree View of the Continuous Improvement Efforts in a Large School of Electrical Engineering and Computer Science

Creator:: Azzouni, Abdullah
Abstract:: Continuous Improvement (CI) of academic computing programs is a main requirement of accreditation. Academic computing programs must have a well-documented CI plan in order to be granted accreditation. Based on the existing literature, we developed a comprehensive CI (or 360-CI) model consisting of 8 components: course, curriculum, administration, faculty, research,...
Resource Type:: Dissertation
Full Text:: [27], Learning Fractals [45], and LEAN/EDU-FOCUS-PDCA [80]. However, Frank et al. presented a

Two Sides of a Coin: Adversarial-Based Image Privacy and Defending Against Adversarial Perturbations for Robust CNNs

Creator:: Rajabi, Arezoo
Abstract:: Emergence of highly accurate Convolutional Neural Networks (CNNs) with the capability to process large datasets, has led to their popularity in many applications, including safety/security-sensitive (e.g. disease recognition, self-driving cars). Despite the high accuracy of convolutional neural networks, they have been found to be susceptible to adversarial noise added to...
Resource Type:: Dissertation

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

Video Analysis : Techniques for Semi-Supervised Video Object Instance Segmentation and Tracking-by-Detection in the Wild

Creator:: Firl, Alrik K.
Abstract:: This thesis consists of two major components. The first part is concerned with video object instance segmentation (VOS), which is the task of assigning per-pixel labels perframe of a video sequence to indicate foreground object instance membership, given the first frame ground truth mask. VOS has myriad applications, from video...
Resource Type:: Masters Thesis
Full Text:: development of the perceptron in 1957 by Frank Rosenblatt [115]. AI and CV have come a long way since their

Fine-Grained Object Recognition Under Limited Training Data

Creator:: Lam, Michael Q.
Abstract:: This dissertation addresses object recognition in challenging settings, where distinct object classes are visually very similar (e.g., species of birds and insects) and/or access to training examples of object classes is limited (e.g., due to the associated high costs of data annotation). In this dissertation, we present a variety of...
Resource Type:: Dissertation

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

Image Based Crypto

Creator:: Basa, Gungor
Abstract:: The ability to create reproducible cryptographically secure keys from temporal environments (e.g., images) has the potential to be a contributor to effective cryptographic mechanisms. Due to the noisy nature of these environments, achieving this goal in a user friendly fashion is a very challenging task, especially since there exists a...
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

ScholarsArchive@OSU

Investigating Latent State and Uncertainty Representations in Reinforcement Learning

On Avoiding Power-Seeking by Artificial Intelligence

A Framework for Evaluating the Comprehensiveness of Continuous Improvement in Academic Computing Programs. A 360-Degree View of the Continuous Improvement Efforts in a Large School of Electrical Engineering and Computer Science

Two Sides of a Coin: Adversarial-Based Image Privacy and Defending Against Adversarial Perturbations for Robust CNNs

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

Video Analysis : Techniques for Semi-Supervised Video Object Instance Segmentation and Tracking-by-Detection in the Wild

Fine-Grained Object Recognition Under Limited Training Data

Object Tracking-by-Segmentation in Videos

Image Based Crypto

Robust and Efficient Classification of Videos in the Wild

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