RI | People | Geoffrey Gordon

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Geoffrey Gordon
Assoc. Res. Professor/Adjunct Faculty RI, MLD (Adjunct)

Email address: ggordon@cs.cmu.edu

Mailing address:
Carnegie Mellon University
Robotics Institute
5000 Forbes Avenue
Pittsburgh, PA 15213

For more information, see my personal homepage.

Jump to: Research interests | Labs & groups | Projects | Publications

Research interests

I'm interested in reinforcement learning, particularly in combination with function approximators.

This section last updated - January 1999.

Current Labs & Groups

Auton Lab - We build practical large-scale deployments of very highly autonomous self-improving systems.

Current Projects [Past projects]

Quality of Life Technology Center - QoLT is a unique partnership between Carnegie Mellon and the University of Pittsburgh that brings together a cross-disciplinary team of technologists, clinicians, industry partners, end users, and other stakeholders to create revolutionary technologies that will improve and sustain the quality of life for all people.

Recent publications [View all 22 publications]

• Decentralized Estimation and Control of Graph Connectivity in Mobile Sensor Networks
  P. Yang, R.A. Freeman, G. Gordon, K. Lynch, S. Srinivasa, and R. Sukthankar
  American Control Conference, June, 2008. [Abstract]
  Download: pdf [177 KB] copyrighted

• A Constraint Generation Approach to Learning Stable Linear Dynamical Systems
  S. Siddiqi, B. Boots, and G. Gordon
  Advances in Neural Information Processing Systems, December, 2007. [Abstract]
  Download: pdf [898 KB], ps.gz [2510 KB] copyrighted

• Adaptive Sampling for Multi-Robot Wide-Area Exploration
  K.H. Low, G. Gordon, J. Dolan, and P. Khosla
  Proceedings of the IEEE 2007 International Conference on Robotics and Automation (ICRA '07), April, 2007. [Abstract]
  Download: pdf [122 KB] copyrighted

• A Latent Space Approach to Dynamic Embedding of Co-occurrence Data
  P. Sarkar, S. Siddiqi, and G. Gordon
  Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AI-STATS), 2007. [Abstract]
  Download: pdf [269 KB], ps.gz [277 KB] copyrighted

• Fast State Discovery for HMM Model Selection and Learning
  S. Siddiqi, G. Gordon, and A. Moore
  Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AI-STATS), 2007. [Abstract]
  Download: pdf [221 KB], ps.gz [240 KB] copyrighted

• Approximate Kalman Filters for Embedding Author-Word Co-occurrence Data over Time
  P. Sarkar, S. Siddiqi, and G. Gordon
  Workshop on Statistical Network Analysis at the Twenty-third International Conference on Machine Learning (ICML), 2006. [Abstract]
  Download: pdf [356 KB] copyrighted

• Adaptive Sampling for Multi-Robot Wide Area Prospecting
  K.H. Low, G. Gordon, J. Dolan, and P. Khosla
  tech. report CMU-RI-TR-05-51, Robotics Institute, Carnegie Mellon University, October, 2005. [Abstract]
  Download: pdf [273 KB] copyrighted

• Anytime Dynamic A*: An Anytime, Replanning Algorithm
  M. Likhachev, D. Ferguson, G. Gordon, A. Stentz, and S. Thrun
  Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), June, 2005. [Abstract]
  Download: pdf [4020 KB] copyrighted

• Anytime Dynamic A*: The Proofs
  M. Likhachev, D. Ferguson, G. Gordon, A. Stentz, and S. Thrun
  tech. report CMU-RI-TR-05-12, Robotics Institute, Carnegie Mellon University, May, 2005. [Abstract]
  Download: pdf [163 KB] copyrighted

• Model uncertainty in classical conditioning
  A. Courville, N.D. Daw, G. Gordon, and D.S. Touretzky
  Advances in NeuralInformation Processing 16, MIT Press, Cambridge, MA, 2005.