Index Catalog // ScholarsArchive@OSU

Computer performance and evaluation utilizating the resource planning and management system

Creator:: Elliott, Jimmie Lynn
Abstract:: A review of current computer performance and evaluation techniques reveals a lack of an acceptable analytic tool for optimal computer system performance and evaluation. A generalized approach to the formulation of a third generation computer system model is proposed. The approach is used to optimize computer resource utilization and to...
Resource Type:: Masters Thesis
Full Text:: privacy Robert A. Short A review of current computer performance and evaluation tech- niques reveals a

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

Active learning with committees : an approach to efficient learning in text categorization using linear threshold algorithms

Creator:: Liere, Ray
Abstract:: We developed and investigated machine learning methods that require minimal preprocessing of the input data, use few training examples, run fast, and still obtain high levels of accuracy. Most approaches to designing machine learning programs are based on the supervised learning paradigm – training examples are chosen randomly and given...
Resource Type:: Dissertation
Full Text:: . Gerald Smith, and Prof. Robert Kiekel. All have shown special patience as I requested permission to do

Efficient training and feature induction in sequential supervised learning

Creator:: Hao, Guohua
Abstract:: Sequential supervised learning problems arise in many real applications. This dissertation focuses on two important research directions in sequential supervised learning: efficient training and feature induction. In the direction of efficient training, we study the training of conditional random fields (CRFs), which provide a flexible and powerful model for sequential...
Resource Type:: Dissertation

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

Detection and Segmentation of Bird Song in Noisy Environments

Creator:: Neal, Lawrence W.
Abstract:: Recent work in machine learning concerns the detection and identification of bird species from audio recordings of their vocalizations. Such analysis can yield valuable ecological information concerning the activity and distribution of species in the wild. Current species-identification methods require individual syllables of bird audio as input, but field-collected audio...
Resource Type:: Honors College Thesis

Exploration of regression models for cancer noncoding mutation recurrence

Creator:: Xu, Tanjin
Abstract:: An important impact of the genome technology revolution will be the elucidation of mechanisms of cancer pathogenesis, leading to improvements in the diagnosis of cancer and the selection of cancer treatment. Integrated with current well-studied massive knowledge and findings about the role of protein-coding mutations in cancer, demystifying the functional...
Resource Type:: Masters Thesis

Semantic image segmentation using domain constraints

Creator:: Roy, Anirban
Abstract:: This dissertation addresses the problem of semantic labeling of image pixels. In the course of our work, we considered different types of semantic labels, including object classes (e.g., car, person), 3D depth values (in the range 0 to 80 meters), and affordance classes (e.g., walkable, sittable). Semantic pixel labeling is...
Resource Type:: Dissertation

Machine learning methods for public policy : simulation, optimization, and visualization

Creator:: McGregor, Sean
Abstract:: Society faces many complex management problems, particularly in the area of shared public resources such as ecosystems. Existing decision making processes are often guided by personal experience and political ideology rather than state-of-the-art scientific understanding. This dissertation envisions a future in which multiple stakeholders are provided with computational tools for...
Resource Type:: Dissertation

Developing a 2D Cross-section Training Strategy for 3D Volume Segmentation by Analyzing Human Perception and Cognitive Tasks

Creator:: Sanandaji, Anahita
Abstract:: 3D volume segmentation is a fundamental process in many scientific and medical applications. Producing accurate segmentations, in an efficient way, is challenging, in part due to low imaging data quality (e.g., noise and low image resolution), and ambiguity in the data that can only be resolved with higher-level knowledge of...
Resource Type:: Dissertation

ScholarsArchive@OSU

Computer performance and evaluation utilizating the resource planning and management system

Expert-gate algorithm

Active learning with committees : an approach to efficient learning in text categorization using linear threshold algorithms

Efficient training and feature induction in sequential supervised learning

Algorithms for massive biological datasets

Detection and Segmentation of Bird Song in Noisy Environments

Exploration of regression models for cancer noncoding mutation recurrence

Semantic image segmentation using domain constraints

Machine learning methods for public policy : simulation, optimization, and visualization

Developing a 2D Cross-section Training Strategy for 3D Volume Segmentation by Analyzing Human Perception and Cognitive Tasks

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