Index Catalog // ScholarsArchive@OSU

Monte Carlo Tree Search with Fixed and Adaptive Abstractions

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

Multi-instance multi-label learning : algorithms and applications to bird bioacoustics

Creator:: Briggs, Forrest
Abstract:: We consider the problem of supervised classification of bird species from audio recordings in a real-world acoustic monitoring scenario (i.e. audio data is collected in the field with an omnidirectional microphone, without human supervision). Obtaining better data about bird activity can assist conservation efforts, and improve our understanding of their...
Resource Type:: Dissertation

Incorporating labeled features into image classification using generalized expectation

Creator:: Moore, Travis
Abstract:: Image classification is a difficult problem, often requiring large training sets to get satisfactory results. However this is a task that humans perform very well, and incorporating user feedback into these learning algorithms could help reduce the dependency on large amounts of labeled training data. This process has already been...
Resource Type:: Masters Thesis

Predicting activity type from accelerometer data

Creator:: Zheng, Yonglei
Abstract:: The study of physical activity is important in improving people’s health as it can help people understand the relationship between physical activity and health. Accelerometers, due to its small size, low cost, convenience and its ability to provide objective information about the frequency, intensity, and duration of physical activity, has...
Resource Type:: Masters Thesis

Algorithms for massive biological datasets

Creator:: Bryant, Douglas W. (Douglas Wesley)
Abstract:: Within the past several years the technology of high-throughput sequencing has transformed the study of biology by offering unprecedented access to life's fundamental building block, DNA. With this transformation's potential a host of brand-new challenges have emerged, many of which lend themselves to being solved through computational methods. From de...
Resource Type:: Dissertation

Some communication algorithms for Gaussian and Eisenstein-Jacobi networks

Creator:: Albader, Bader
Abstract:: Interconnection networks play important roles in designing high performance computers. Recently two new classes of interconnection networks based on the concept of Gaussian and Eisenstein-Jacobi integers were introduced. In this research, efficient routing and broadcasting algorithms for these networks are developed. Furthermore, constructing edge disjoint Hamiltonian cycles in Gaussian networks...
Resource Type:: Dissertation

Structured gradient boosting

Creator:: Parker, Charles (Charles Lincoln)
Abstract:: The goal of many machine learning problems can be formalized as the creation of a function that can properly classify an input vector, given a set of examples of that function. While this formalism has produced a number of success stories, there are notable situations in which it fails. One...
Resource Type:: Dissertation

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

Contributions to Collaborative Filtering Research

Creator:: Nong, Shuzhen
Abstract:: In this report, I first introduce three areas of interest to collaborative filtering researchers, namely: (a) how to solve the sparsity and scalability problems in recommendation systems; (b) how to rapidly develop and test collaborative filtering algorithms; and (c) how to apply collaborative filtering to unbounded numeric preference data. In...
Resource Type:: Capstone Project

Timing Attacks on Software Implementation of RSA

Creator:: Singh, Harshman
Abstract:: Timing attacks enable an attacker to extract secret information from a cryptosystem by observing timing differences with respect to different inputs given to an encryption or decryption algorithm. Werner Schindler has proposed a timing attack on smart card devices. We implemented this attack based on the same approach for RSA...
Resource Type:: Capstone Project

Exact learning of tree patterns

Creator:: Amoth, Thomas R.
Abstract:: Tree patterns are natural candidates for representing rules and hypotheses in many tasks such as information extraction and symbolic mathematics. A tree pattern is a tree with labeled nodes where some of the leaves may be labeled with variables, whereas a tree instance has no variables. A tree pattern matches...
Resource Type:: Dissertation

Learning classification rules by randomized iterative local search

Creator:: Chisholm, Michael (Michael Andrew), 1974-
Abstract:: Learning easily understandable decision rules from examples is one of the classic problems in machine learning. Most learning algorithms for this problem employ some variation of a greedy separate-and-conquer algorithm. In this paper, we describe a system called LERILS that learns highly accurate and comprehensible rules from examples using a...
Resource Type:: Masters Thesis

System reliability through Algorithm-Based Fault tolerance and reconfiguration

Creator:: Ramanathan, Gowri
Resource Type:: Dissertation

Fault-tolerant communications in parallel systems

Creator:: Park, Seungjin
Resource Type:: Dissertation

Expert-gate algorithm

Creator:: Joshi, Varad Vidyadhar
Abstract:: The goal of Inductive Learning is to produce general rules from a set of seen examples, which can then be applied to other unseen examples. ID3 is an inductive learning algorithm that can be used for the classification task. The input to the algorithm is a set of tuples of...
Resource Type:: Masters Thesis

Concept coverage and its application to two learning tasks

Creator:: Almuallim, Hussein Saleh
Abstract:: The coverage of a learning algorithm is the number of concepts that can be learned by that algorithm from samples of a given size for given accuracy and confidence parameters. This thesis begins by asking whether good learning algorithms can be designed by maximizing their coverage. There are three questions...
Resource Type:: Dissertation

ScholarsArchive@OSU

Monte Carlo Tree Search with Fixed and Adaptive Abstractions

Multi-instance multi-label learning : algorithms and applications to bird bioacoustics

Incorporating labeled features into image classification using generalized expectation

Predicting activity type from accelerometer data

Algorithms for massive biological datasets

Some communication algorithms for Gaussian and Eisenstein-Jacobi networks

Structured gradient boosting

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

Contributions to Collaborative Filtering Research

Timing Attacks on Software Implementation of RSA

Exact learning of tree patterns

Learning classification rules by randomized iterative local search

System reliability through Algorithm-Based Fault tolerance and reconfiguration

Fault-tolerant communications in parallel systems

Expert-gate algorithm

Concept coverage and its application to two learning tasks

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