Schneider, Jeff - Robotics Institute, School of Computer Science, Carnegie Mellon University

• Classi cation-Driven Pathological Neuroimage Retrieval Using Statistical Asymmetry Measures
• MAPPING THE COSMOLOGICAL CONFIDENCE BALL SURFACE Brent Bryan and Jeff Schneider
• Category: Control, Navigation and Planning Preference: Oral presentation
• Covariant Policy Search J. Andrew Bagnell and Jeff Schneider
• Registration between 3D images of human anatomies enables crosssubject diagnosis. However, innate differences in the appearance and location of anatomical structures between individuals make accurate registration difficult. We characterize
• Active Learning in Discrete Input Spaces Je Schneider Andrew Moore
• Approximate Solutions For Partially Observable Stochastic Games with Common Payoffs
• Cooperative Coaching in Robot Learning Jeff G. Schneider Christopher M. Brown
• Active Learning on NonStationary Functions Jeff Schneider
• cGraph: A Fast GraphBased Method for Link Analysis and Queries Jeremy Kubica Andrew Moore David Cohn Jeff Schneider
• Robot Skill Learning Through Intelligent Experimentation
• Automatic Construction of Active Appearance Models as an Image Coding Problem
• A Probabilistic Framework to Learn from Multiple Annotators with Time-Varying Accuracy
• Efficient Search for Robot Skill Learning: Simulation and Reality Jeff G. Schneider and Roger F. Gans
• Learning Compressible Models Jeff Schneider
• Category: Control, Navigation and Planning Preference: Oral presentation
• Efficient Locally Weighted Polynomial Regression Predictions Andrew W. Moore
• Tractable Group Detection on Large Link Data Sets Jeremy Kubica
• Q2: Memorybased active learning for optimizing noisy continuous functions
• Value Function Based Production Scheduling Jeff G. Schneider \Lambda Justin A. Boyan
• Autonomous Helicopter Control using Reinforcement Learning Policy Search Methods
• Learning Opportunity Costs in MultiRobot Market Based Planners
• Actively Learning Level-Sets of Composite Functions Brent Bryan BRENT@GOOGLE.COM
• Real-valued All-Dimensions search: Low-overhead rapid searching over subsets of attributes
• Projection Penalties: Dimension Reduction without Loss Yi Zhang yizhang1@cs.cmu.edu
• Learning Nonlinear Dynamic Models from Non-sequenced Data Tzu-Kuo Huang Le Song Jeff Schneider
• Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization
• Learning Linear Dynamical Systems without Sequence Information Tzu-Kuo Huang tzukuoh@cs.cmu.edu
• Detecting Anomalous Records in Categorical Datasets Kaustav Das
• Belief State Approaches to Signaling Alarms in Surveillance Systems
• Policy search by dynamic programming J. Andrew Bagnell
• Finding Underlying Connections: A Fast Graph-Based Method for Link Analysis and Collaboration Queries
• Stochastic Link and Group Detection Jeremy Kubica
• Adapting Control Policies for Expensive Systems to Changing Environments Matthew Tesch, Jeff Schneider, and Howie Choset
• Nonparametric Divergence Estimation with Applications to Machine Learning on Distributions
• On the Estimation of -Divergences Barnabs Pczos Jeff Schneider
• Using Response Surfaces and Expected Improvement to Optimize Snake Robot Gait Parameters
• Multi-Label Output Codes using Canonical Correlation Analysis Yi Zhang Jeff Schneider
• Learning Multiple Tasks with a Sparse Matrix-Normal Penalty
• NONPARAMETRIC DIVERGENCE ESTIMATORS FOR INDEPENDENT SUBSPACE ANALYSIS
• Hierarchical Probabilistic Models for Group Anomaly Detection Liang Xiong Barnabas Poczos Jeff Schneider
• Learning Auto-regressive Models from Sequence and Non-sequence Data
• The Astronomical Journal, 142:203 (10pp), 2011 December doi:10.1088/0004-6256/142/6/203 C 2011. The American Astronomical Society. All rights reserved. Printed in the U.S.A.
• Group Anomaly Detection using Flexible Genre Models Liang Xiong
• Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled Text