Now showing items 1-6 of 6
Learning without labels and nonnegative tensor factorization
(Georgia Institute of Technology, 2010-04-08)
Supervised learning tasks like building a classifier, estimating the error rate of the predictors, are typically performed with labeled data. In most cases, obtaining labeled data is costly as it requires manual labeling. ...
Segmental discriminative analysis for American Sign Language recognition and verification
(Georgia Institute of Technology, 2010-04-06)
This dissertation presents segmental discriminative analysis techniques for American Sign Language (ASL) recognition and verification. ASL recognition is a sequence classification problem. One of the most successful ...
Task transparency in learning by demonstration : gaze, pointing, and dialog
(Georgia Institute of Technology, 2010-07-07)
This body of work explores an emerging aspect of human-robot interaction, transparency. Socially guided machine learning has proven that highly immersive robotic behaviors have yielded better results than lesser interactive ...
Domain knowledge, uncertainty, and parameter constraints
(Georgia Institute of Technology, 2010-08-24)
Communication and alignment of grounded symbolic knowledge among heterogeneous robots
(Georgia Institute of Technology, 2010-04-05)
Experience forms the basis of learning. It is crucial in the development of human intelligence, and more broadly allows an agent to discover and learn about the world around it. Although experience is fundamental to ...
Applying inter-layer conflict resolution to hybrid robot control architectures
(Georgia Institute of Technology, 2010-01-20)
In this document, we propose and examine the novel use of a learning mechanism between the reactive and deliberative layers of a hybrid robot control architecture. Balancing the need to achieve complex goals and meet ...