Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Computer Sciences (50)
- Artificial Intelligence and Robotics (29)
- Engineering (21)
- Statistics and Probability (10)
- Data Science (8)
-
- Computer Engineering (7)
- Life Sciences (5)
- Other Computer Sciences (5)
- Theory and Algorithms (5)
- Electrical and Computer Engineering (4)
- Applied Mathematics (3)
- Bioinformatics (3)
- Mathematics (3)
- Medicine and Health Sciences (3)
- Statistical Models (3)
- Applied Statistics (2)
- Arts and Humanities (2)
- Business (2)
- Databases and Information Systems (2)
- Environmental Sciences (2)
- Graphics and Human Computer Interfaces (2)
- Mechanical Engineering (2)
- Multivariate Analysis (2)
- Music (2)
- Other Applied Mathematics (2)
- Other Computer Engineering (2)
- Other Statistics and Probability (2)
- Signal Processing (2)
- Acoustics, Dynamics, and Controls (1)
- Institution
Articles 61 - 64 of 64
Full-Text Articles in Physical Sciences and Mathematics
Effective Task Transfer Through Indirect Encoding, Phillip Verbancsics
Effective Task Transfer Through Indirect Encoding, Phillip Verbancsics
Electronic Theses and Dissertations
An important goal for machine learning is to transfer knowledge between tasks. For example, learning to play RoboCup Keepaway should contribute to learning the full game of RoboCup soccer. Often approaches to task transfer focus on transforming the original representation to fit the new task. Such representational transformations are necessary because the target task often requires new state information that was not included in the original representation. In RoboCup Keepaway, changing from the 3 vs. 2 variant of the task to 4 vs. 3 adds state information for each of the new players. In contrast, this dissertation explores the idea …
Predicting Flavonoid Ugt Regioselectivity With Graphical Residue Models And Machine Learning., Arthur Rhydon Jackson
Predicting Flavonoid Ugt Regioselectivity With Graphical Residue Models And Machine Learning., Arthur Rhydon Jackson
Electronic Theses and Dissertations
Machine learning is applied to a challenging and biologically significant protein classification problem: the prediction of flavonoid UGT acceptor regioselectivity from primary protein sequence. Novel indices characterizing graphical models of protein residues are introduced. The indices are compared with existing amino acid indices and found to cluster residues appropriately. A variety of models employing the indices are then investigated by examining their performance when analyzed using nearest neighbor, support vector machine, and Bayesian neural network classifiers. Improvements over nearest neighbor classifications relying on standard alignment similarity scores are reported.
Concept Learning By Example Decomposition, Sameer Joshi
Concept Learning By Example Decomposition, Sameer Joshi
Electronic Theses and Dissertations
For efficient understanding and prediction in natural systems, even in artificially closed ones, we usually need to consider a number of factors that may combine in simple or complex ways. Additionally, many modern scientific disciplines face increasingly large datasets from which to extract knowledge (for example, genomics). Thus to learn all but the most trivial regularities in the natural world, we rely on different ways of simplifying the learning problem. One simplifying technique that is highly pervasive in nature is to break down a large learning problem into smaller ones; to learn the smaller, more manageable problems; and then to …
Towards A Self-Calibrating Video Camera Network For Content Analysis And Forensics, Imran Junejo
Towards A Self-Calibrating Video Camera Network For Content Analysis And Forensics, Imran Junejo
Electronic Theses and Dissertations
Due to growing security concerns, video surveillance and monitoring has received an immense attention from both federal agencies and private firms. The main concern is that a single camera, even if allowed to rotate or translate, is not sufficient to cover a large area for video surveillance. A more general solution with wide range of applications is to allow the deployed cameras to have a non-overlapping field of view (FoV) and to, if possible, allow these cameras to move freely in 3D space. This thesis addresses the issue of how cameras in such a network can be calibrated and how …