Carnegie Mellon University

School of Computer Science

Language Technologies Institute

SELECTED PRESENTATIONS

• Data-Intensive Scalability in Machine Learning and Computational Proteomics – Jaime Carbonell et al – January 2009
  
  

• Computational Biology at Carnegie Mellon University – Jaime Carbonell – December 2008

• Computational Proteomics: Structure/Function Prediction & the Protein Interactome – Jaime Carbonell, with Betty Cheng, Yan Liu, Eric Xing, Yanjun Qi, Judith Klein-Seetharaman, and Oznur Tastan – December 2008

• Machine Learning Part 2: Intermediate and Active Sampling Methods – Jaime Carbonell, with Pinar Donmez and Jingrui He – December 2008

• Machine Learning & Data Mining Part 1: The Basics – Jaime Carbonell, with Tom Mitchell, Sebastian Thrun, and Yiming Yang – December 2008

• Proactive Learning: Cost-Sensitive Active Learning with Multiple Imperfect Oracles – Jaime Carbonell and Pinar Donmez – October 2008

• Active Learning Seminar – Jaime Carbonell and All Participants – Fall 2008

• Introduction to the Language Technologies Institute – Jaime Carbonell – Fall 2008

• Optimizing Estimated Loss Reduction for Active Sampling in Rank Learning – Pinar Donmez and Jaime Carbonell – June 2008

• Bridging the Gap: Teaching and Assessing Spoken English – Carnegie Speech – February 2008

• Machine Translation & Automated Speech Recognition – Jaime Carbonell, with Richard Stern and Alex Rudnicky – February 2008

• Paired Sampling in Density-Sensitive Active Learning - Pinar Donmez, with Jaime Carbonell – January 2008

• Understanding the Language of Virus Proteins to Automatically Detect Drug Resistance – Betty Cheng and Jaime Carbonell – January 2008

• Dual Strategy Active Learning – Pinar Donmez, with Jaime Carbonell and Paul Bennett – December 2007

• Challenges for Information Fusion in Retrieval – Jaime Carbonell – May 2007

• NSF - Relevant Challenges in Computational Intelligence – Jaime Carbonell, Tom Mitchell, Guy Bleloch, Randy Bryant, et al – April 2007

• Protein Tertiary and Quaternary Fold Recognition: A ML Approach – Jaime Carbonell, with Yan Liu, Vanathi Gopalakrishnan, and Peter Weigele – April 2007

• New Paradigms for MT and IR – Jaime Carbonell – March 2007

• Protein Quaternary Fold Recognition Using Conditional Graphical Models – Yan Liu, Jaime Carbonell, Vanathi Gopalakrishnan, and Peter Weigele – January 2007

• Research Problems in Digital Libraries: Data Mining and Text Mining – Jaime Carbonell and Raj Reddy – April 2006

• Segmentation Conditional Random Fields (SCRFs): A New Approach for Protein Fold Recognition – Yan Liu, Jaime Carbonell, Peter Weigele, and Vanathi Gopalakrishnan – May 2005