Index Catalog // ScholarsArchive@OSU

Creator:: Hostetler, Jesse A.
Abstract:: Monte Carlo tree search (MCTS) is a class of online planning algorithms for Markov decision processes (MDPs) and related models that has found success in challenging applications. In the online planning approach, the agent makes a decision in the current state by performing a limited forward search over possible futures...
Resource Type:: Dissertation
Full Text:: Carlo Tree Search with Fixed and Adaptive Abstractions Abstract approved: Thomas G. Dietterich Alan P

Creator:: Shen, Jianqiang
Abstract:: Knowledge workers are struggling in the information flood. There is a growing interest in intelligent desktop environments that help knowledge workers organize their daily life. Intelligent desktop environments allow the desktop user to define a set of “activities” that characterize the user’s desktop work. These environments then attempt to identify...
Resource Type:: Dissertation
Full Text:: supportive and patient with me during the past 5 years. I would like to thank my committee members, Alan

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:: conferences. I am very grateful to Dr. Alan Fern for providing feedback and discussing research ideas during

Creator:: Sorower, Mohammad Shahed
Abstract:: Machine learning systems are generally trained offline using ground truth data that has been labeled by experts. However, these batch training methods are not a good fit for many applications, especially in the cases where complete ground truth data is not available for offline training. In addition, batch methods do...
Resource Type:: Dissertation
Full Text:: committee members: Prof. Prasad Tadepalli, Prof. Alan Fern, Prof. Xiaoli Fern and Prof. Harry Yeh, for

Creator:: Dodge, Jonathan E.
Abstract:: Assessing AI systems is difficult. Humans rely on AI systems in increasing ways, both visible and invisible, meaning a variety of stakeholders need a variety of assessment tools (e.g., a professional auditor, a developer, and an end user all have different needs). We posit that it is possible to provide...
Resource Type:: Dissertation
Full Text:: who kept us on the proper statistical path; Alan Fern, who wrangled grant funders and taught us all

Creator:: Emmott, Andrew F.
Abstract:: It is common practice in the unsupervised anomaly detection literature to create experimental benchmarks by sampling from existing supervised learning datasets. We seek to improve this practice by identifying four dimensions important to real-world anomaly detection applications --- point difficulty, clusteredness of anomalies, relevance of features, and relative frequency of...
Resource Type:: Masters Thesis
Full Text:: Shubhomoy Das, Thomas Dietterrich, Alan Fern and Weng-Keen Wong as authors. The contributions of Shubhomoy

Creator:: Ruff, Ritchey Alvin
Abstract:: A key aspect of how we understand the world revolves around an ability to manipulate our surroundings to experiment. From the scientific method through theories of child development, the ability to experiment is deemed critical; however, few studies have been performed to understand the strengths and weaknesses of different experimental...
Resource Type:: Dissertation
Full Text:: , Carol Lee). Many an evening was spent at the bar proof-reading the latest draft or debugging the latest

ScholarsArchive@OSU