Autumn School 2006: Machine Learning over Text and Images - Pittsburgh
Machine learning approaches to natural language processing problems such as information retrieval, document classification, and information extraction have developed rapidly over recent years. Even more recently, the joint analysis of text and images has become a significant focus for machine learning. This autumn school will summarize the state of the art in machine learning for text analysis and for joint text/image analysis, as presented by researchers active in these fields. It is intended for students who already have a familiarity with machine learning, and is designed for software developers, graduate students, and advanced researchers with an interest in learning more about this area.
Introduction
Introduction to the Machine Learning over Text & Images - Autumn School by Eric ...
Feb 25, 2007 14598 views
Lectures
Image Analysis
Feb 25, 2007 12337 views
Semisupervised Learning Approaches
Feb 25, 2007 85155 views
Undirected Graphical Models for Text & Image
Feb 25, 2007 6849 views
Text Information Extraction
Feb 25, 2007 34036 views
Generative Models for Visual Objects and Object Recognition via Bayesian Inferen...
Feb 25, 2007 69143 views
Generative Latent Space Models for Text and Image
Feb 25, 2007 9334 views
Joint Mining of Biological Text and Images: Case Studies
Feb 25, 2007 6611 views
Text Classification
Feb 25, 2007 53048 views
Interviews
Interview with Tom Mitchell
Feb 25, 2007 75164 views
Interview with Kamal Nigam
Feb 25, 2007 6565 views
Interview with Eric Xing
Feb 25, 2007 9420 views
Interview with Robert Murphy
Feb 25, 2007 4592 views
Interview with Christos Faloutsos
Feb 25, 2007 7108 views
Interview with Fei-Fei Li
Feb 25, 2007 20408 views
