Index Catalog // ScholarsArchive@OSU

A Benchmarking Study of Unsupervised Anomaly Detection Algorithms

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

A C* development environment for the Meiko CS-2 multicomputer

Creator:: Zhang, Chung
Abstract:: With sequential computing technology reaching its speed limits, parallel processing is emerging as the key to very-high-speed computation. However, developing a parallel program is by no means a simple task; neither is analyzing the performance of parallel programs. C* is a high-level data-parallel language that hides explicit message passing and...
Resource Type:: Capstone Project

A collaborative filtering algorithm and evaluation metric that accurately model the user experience

Creator:: McLaughlin, Matthew
Abstract:: "Collaborative filtering algorithms’ performances have been evaluated using a variety of metrics. These metrics, such as Mean Absolute Error and Precision, have often ignored recommendations for which they do not have data. Ignoring these recommendations has provided numbers which do not accurately represent the user experience. Qualitatively we have seen...
Resource Type:: Capstone Project

A Distributed Scheme for Accelerating and Scaling PSPNet

Creator:: Krishna, Ajay
Abstract:: Advances in deep learning based image processing have led to their adoption for a wide range of applications, and in tow with these developments is a dramatic increase in the availability of high quality datasets. With this comes the need to accelerate and scale deep learning applications in order to...
Resource Type:: Masters Thesis

A numerical approach to Tamme's problem in euclidean n-space

Creator:: Adams, Patrick Guy
Resource Type:: Masters Thesis

A SAT-based planning framework for optimizing resource production

Creator:: Ventura, Christopher
Abstract:: Domain-independent automated planning is concerned with computing a sequence of actions that can transform an initial state into a desired goal state. Resource production domains form an interesting class of such problems, in that they typically require reasoning about concurrent durative-actions with continuous effects while minimizing some cost function. Although...
Resource Type:: Masters Thesis

A Study of Temporal Convolutional Neural Networks for Music Language Modeling as Applied to Automatic Music Transcription

Creator:: Meyn, Matthew
Abstract:: Automatic music transcription (AMT) is the task, given an acoustic representation of music, to recover a symbolic notation of the written notes expressed by the sound. Transcribing music with multiple notes sounding simultaneously is difficult for both humans and machines. Much existing work on AMT has focused on suitable acoustic...
Resource Type:: Capstone Project

A study on student perceptions of principles of logic and their application to the principle of mathematical induction

Creator:: Boone, Allan R.
Abstract:: The purpose of this article is to explore student reasoning with regard to problems in logic, particularly those related to the Principle of Mathematical Induction (PMI). The five case studies presented build off of work done by other researchers, most notably Dubinsky and Harel, who both looked at how students'...
Resource Type:: Masters Thesis

Active learning of constraints for semi-supervised clustering

Creator:: Xiong, Sicheng
Abstract:: Semi-supervised clustering aims to improve clustering performance by considering user supervision in the form of pairwise constraints. In this paper, we study the active learning problem of selecting pairwise must-link and cannot-link constraints for semisupervised clustering. We consider active learning in an iterative manner where in each iteration queries are...
Resource Type:: Masters Thesis

Adiabatic Markov Decision Process : convergence of value iteration algorithm

Creator:: Duong, Thai
Abstract:: Markov Decision Process (MDP) is a well-known framework for devising the optimal decision making strategies under uncertainty. Typically, the decision maker assumes a stationary environment which is characterized by a time-invariant transition probability matrix. However, in many real-world scenarios, this assumption is not justified, thus the optimal strategy might not...
Resource Type:: Masters Thesis

ScholarsArchive@OSU

A Benchmarking Study of Unsupervised Anomaly Detection Algorithms

A C* development environment for the Meiko CS-2 multicomputer

A collaborative filtering algorithm and evaluation metric that accurately model the user experience

A Distributed Scheme for Accelerating and Scaling PSPNet

A numerical approach to Tamme's problem in euclidean n-space

A SAT-based planning framework for optimizing resource production

A Study of Temporal Convolutional Neural Networks for Music Language Modeling as Applied to Automatic Music Transcription

A study on student perceptions of principles of logic and their application to the principle of mathematical induction

Active learning of constraints for semi-supervised clustering

Adiabatic Markov Decision Process : convergence of value iteration algorithm

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