Home/Jeff Schneider

Jeff Schneider

Research Professor
Email: jeff4@andrew.cmu.edu
Office: NSH 3117
Phone: (412) 268-2339
Personal Homepage: http://www.cs.cmu.edu/~schneide
Administrative Assistant: Karen R. Widmaier

My research is in active learning, data mining,reinforcement learning, optimization, and intelligent control. My efforts are focused on the application of these methods to real world industrial and commercial problems.

Displaying 45 Publications
Active Area Search via Bayesian Quadrature
Yifei Ma, Roman M. Garnett and Jeff Schneider

Conference Paper, Carnegie Mellon University, Artificial Intelligence and Statistics (AISTATS), March, 2015
Active Area Search via Bayesian Quadrature
Yifei Ma, Roman M. Garnett and Jeff Schneider

Conference Paper, Artificial Intelligence and Statistics (AISTATS), January, 2015
A FIRST LOOK AT CREATING MOCK CATALOGS WITH MACHINE LEARNING TECHNIQUES
Xiaoying Xu, Shirley Ho, Hy Trac, Jeff Schneider, Barnabas Poczos and Michelle Ntampaka

Journal Article, The Astrophysical Journal, January, 2014
Learning from Point Sets with Observational Bias
Liang Xiong and Jeff Schneider

Journal Article, Uncertainty in Artificial Intelligence (UAI), January, 2014
Expensive Function Optimization with Stochastic Binary Outcomes
Matthew Tesch, Jeff Schneider and Howie Choset

Conference Paper, Carnegie Mellon University, International Conference on Machine Learning (Atlanta, June 16-21 2013), June, 2013
Learning Stochastic Binary Tasks using Bayesian Optimization with Shared Task Knowledge
Matthew Tesch, Jeff Schneider and Howie Choset

Conference Paper, Carnegie Mellon University, International Conference on Machine Learning: Workshop on Robot Learning (Atlanta, June 16-21 2013), June, 2013
Expensive Multiobjective Optimization for Robotics
Matthew Tesch, Jeff Schneider and Howie Choset

Conference Paper, Carnegie Mellon University, International Conference on Robotics and Automation (Karlsruhe, Germany, May 6-10 2013), May, 2013
Expensive Multiobjective Optimization and Validation with a Robotics Application
Matthew Tesch, Jeff Schneider and Howie Choset

Conference Paper, Carnegie Mellon University, Neural Information Processing Systems: Workshop on Bayesian Optimization & Decision Making, December, 2012
Environmentally adaptive control policies for expensive systems
Matthew Tesch, Jeff Schneider and Howie Choset

Conference Paper, Carnegie Mellon University, International Conference on Climbing and Walking Robots, July, 2012
Adapting Control Policies for Expensive Systems to Changing Environments
Matthew Tesch, Jeff Schneider and Howie Choset

Conference Paper, Carnegie Mellon University, Neural Information Processing Systems: Workshop on Bayesian Optimization, Experimental Design, and Bandits, December, 2011
Adapting Control Policies for Expensive Systems to Changing Environments
Matthew Tesch, Jeff Schneider and Howie Choset

Conference Paper, Carnegie Mellon University, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September, 2011
Using Response Surfaces and Expected Improvement to Optimize Snake Robot Gait Parameters
Matthew Tesch, Jeff Schneider and Howie Choset

Conference Paper, Carnegie Mellon University, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1069 - 1074, September, 2011
Alias Detection in Link Data Sets
Paul Hsiung, Andrew Moore, Daniel Neill and Jeff Schneider

Conference Paper, Carnegie Mellon University, Proceedings of the International Conference on Intelligence Analysis, May, 2005
Learning Opportunity Costs in Multi-Robot Market Based Planners
Jeff Schneider, David Apfelbaum, J. Andrew (Drew) Bagnell and Reid Simmons

Conference Paper, Carnegie Mellon University, April, 2005
Automatic Construction of Active Appearance Models as an Image Coding Problem
Simon Baker, Iain Matthews and Jeff Schneider

Journal Article, Carnegie Mellon University, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 26, No. 10, pp. 1380 - 1384, October, 2004
Semantic based Biomedical Image Indexing and Retrieval
Yanxi Liu, Nicole Lazar, W.E. Rothfus, Frank Dellaert, Andrew Moore, Jeff Schneider and Takeo Kanade

Book Section/Chapter, Carnegie Mellon University, Trends and Advances in Content-Based Image and Video Retrieval, February, 2004
Policy Search by Dynamic Programming
J. Andrew (Drew) Bagnell, Sham Kakade, Andrew Ng and Jeff Schneider

Conference Paper, Carnegie Mellon University, Neural Information Processing Systems, Vol. 16, December, 2003
Policy Search in Reproducing Kernel Hilbert Space
J. Andrew (Drew) Bagnell and Jeff Schneider

Tech. Report, CMU-RI-TR-03-45, Robotics Institute, Carnegie Mellon University, November, 2003
Tractable Group Detection on Large Link Data Sets
Jeremy Martin Kubica, Andrew Moore and Jeff Schneider

Conference Paper, Carnegie Mellon University, The Third IEEE International Conference on Data Mining, pp. 573-576, November, 2003
K-groups: Tractable Group Detection on Large Link Data Sets
Jeremy Martin Kubica, Andrew Moore and Jeff Schneider

Tech. Report, CMU-RI-TR-03-32, Robotics Institute, Carnegie Mellon University, September, 2003
cGraph: A Fast Graph-Based Method for Link Analysis and Queries
Jeremy Martin Kubica, Andrew Moore, David Cohn and Jeff Schneider

Conference Paper, Carnegie Mellon University, Proceedings of the 2003 IJCAI Text-Mining & Link-Analysis Workshop, pp. 22-31, August, 2003
Covariant Policy Search
J. Andrew (Drew) Bagnell and Jeff Schneider

Conference Paper, Carnegie Mellon University, Proceeding of the International Joint Conference on Artifical Intelligence, August, 2003
Finding Underlying Connections: A Fast Graph-Based Method for Link Analysis and Collaboration Queries
Jeremy Martin Kubica, Andrew Moore, David Cohn and Jeff Schneider

Conference Paper, Carnegie Mellon University, Proceedings of the 2003 International Conference on Machine Learning, pp. 392-399, August, 2003
Image Coding with Active Appearance Models
Simon Baker, Iain Matthews and Jeff Schneider

Tech. Report, CMU-RI-TR-03-13, Robotics Institute, Carnegie Mellon University, April, 2003
Stochastic Link and Group Detection
Jeremy Martin Kubica, Andrew Moore, Jeff Schneider and Yiming Yang

Conference Paper, Carnegie Mellon University, The Eighteenth National Conference on Artificial Intelligence, pp. 798-804, August, 2002
Classification-Driven Pathological Neuroimage Retrieval Using Statistical Asymmetry Measures
Yanxi Liu, Frank Dellaert, William E. Rothfus, Andrew Moore, Jeff Schneider and Takeo Kanade

Conference Paper, Carnegie Mellon University, Proceedings of the 2001 Medical Imaging Computing and Computer Assisted Intervention Conference (MICCAI '01), October, 2001
Solving Uncertain Markov Decision Problems
J. Andrew (Drew) Bagnell, Andrew Y. Ng and Jeff Schneider

Tech. Report, CMU-RI-TR-01-25, Robotics Institute, Carnegie Mellon University, August, 2001
Autonomous Helicopter Control using Reinforcement Learning Policy Search Methods
J. Andrew (Drew) Bagnell and Jeff Schneider

Conference Paper, Carnegie Mellon University, Proceedings of the International Conference on Robotics and Automation 2001, May, 2001
Q2: memory-based active learning for optimizing noisy continuous functions
Andrew Moore, Jeff Schneider, Justin Boyan and M.S. Lee

Conference Paper, Carnegie Mellon University, IEEE International Conference on Robotics and Automation (ICRA '00), Vol. 4, pp. 4095 - 4102, April, 2000
A Locally Weighted Learning Tutorial using Vizier 1.0
Jeff Schneider and Andrew Moore

Tech. Report, CMU-RI-TR-00-18, Robotics Institute, Carnegie Mellon University, February, 2000
3-D Deformable Registration of Medical Images Using a Statistical Atlas
Mei Chen, Takeo Kanade, Dean Pomerleau and Jeff Schneider

Conference Paper, September, 1999
Cached Sufficient Statistics for Automated Mining and Discovery from Massive Data Sources
Andrew Moore, Jeff Schneider, Brigham Anderson, Scott Davies, Paul Komarek, Mary Soon Lee, Marina Meila, Remi Munos, Kary Myers and Dan Pelleg

Miscellaneous, July, 1999
Probabilistic Registration of 3-D Medical Images
Mei Chen, Takeo Kanade, Dean Pomerleau and Jeff Schneider

Tech. Report, CMU-RI-TR-99-16, Robotics Institute, Carnegie Mellon University, July, 1999
Distributed Value Functions
Jeff Schneider, Weng-Keen Wong, Andrew Moore and Martin Riedmiller

Conference Paper, International Conference on Machine Learning, January, 1999
3-D Deformable Registration of Medical Images Using a Statistical Atlas
Mei Chen, Takeo Kanade, Dean Pomerleau and Jeff Schneider

Tech. Report, CMU-RI-TR-98-35, Robotics Institute, Carnegie Mellon University, Proceedings of the Second International Conference on Medical Imag Computing & Computer-Assisted Intervention, December, 1998
Stochastic production scheduling to meet demand forecasts
Jeff Schneider, Justin Boyan and Andrew Moore

Conference Paper, Proceedings of the 37th IEEE Conference on Decision and Control, Vol. 3, pp. 2722 - 2727, December, 1998
Q2: Memory-based active learning for optimizing noisy continuous functions
Andrew Moore, Jeff Schneider, Justin Boyan and Mary Lee

Conference Paper, International Conference of Machine Learning, June, 1998
Value Function Based Production Scheduling
Jeff Schneider, Justin Boyan and Andrew Moore

Conference Paper, Machine Learning: Proceedings of the Fifteenth International Conference (ICML '98), March, 1998
Efficient Locally Weighted Polynomial Regression Predictions
Andrew Moore, Jeff Schneider and Kan Deng

Conference Paper, International Conference on Machine Learning, January, 1997
Active Learning on Non-Stationary Functions
Jeff Schneider

Conference Paper, Working Notes of the AAAI Fall Symposium on Active Learning, January, 1996
Exploiting Model Uncertainty Estimates for Safe Dynamic Control Learning
Jeff Schneider

Conference Paper, Neural Information Processing Systems 9, January, 1996
Cooperative Coaching in Robot Learning
Jeff Schneider and Christopher M. Brown

Conference Paper, International Conference on Intelligent Robots and Systems, January, 1995
Memory-based Stochastic Optimization
Andrew Moore and Jeff Schneider

Conference Paper, Neural Information Processing Systems 8, January, 1995
Multiresolution Instance-Based Learning
Andrew Moore, Jeff Schneider and Kan Deng

Conference Paper, Proceedings of International Joint Conference on Artificial Intelligence, January, 1995
Efficient Search for Robot Skill Learning: Simulation and Reality
Jeff Schneider and Roger F. Gans

Conference Paper, International Conference on Intelligent Robots and Systems, January, 1994
Mailing Address
Carnegie Mellon University
Robotics Institute
5000 Forbes Avenue
Pittsburgh, PA 15213
2017-09-13T10:48:42+00:00