Jeff G. Schneider

156 papers A* 47A 31B 1Misc 2Journal 48Unranked 27

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Cost-Aware Diffusion Active Search. CoRR Arundhati Banerjee, Jeff G. Schneider
2026	J	`jnl`	Maximum Likelihood Reinforcement Learning. CoRR Fahim Tajwar, Guanning Zeng, Yueer Zhou, Yuda Song, Daman Arora, Yiding Jiang, Jeff G. Schneider, Ruslan Salakhutdinov, Haiwen Feng, Andrea Zanette
2026	J	`jnl`	Retrospective In-Context Learning for Temporal Credit Assignment with Large Language Models. CoRR Wen-Tse Chen, Jiayu Chen, Fahim Tajwar, Hao Zhu, Xintong Duan, Ruslan Salakhutdinov, Jeff G. Schneider
2026	J	`jnl`	TADPO: Reinforcement Learning Goes Off-road. CoRR Zhouchonghao Wu, Raymond Song, Vedant Mundheda, Luis E. Navarro-Serment, Christof Schoenborn, Jeff G. Schneider
2025	J	`jnl`	Accelerated Online Reinforcement Learning using Auxiliary Start State Distributions. CoRR Aman Mehra, Alexandre Capone, Jeff G. Schneider
2025	J	`jnl`	Accelerating Diffusion Models in Offline RL via Reward-Aware Consistency Trajectory Distillation. CoRR Xintong Duan, Yutong He, Fahim Tajwar, Ruslan Salakhutdinov, J. Zico Kolter, Jeff G. Schneider
2025	J	`jnl`	CaRT: Teaching LLM Agents to Know When They Know Enough. CoRR Grace Liu, Yuxiao Qu, Jeff G. Schneider, Aarti Singh, Aviral Kumar
2025	J	`jnl`	Can Large Reasoning Models Self-Train? CoRR Sheikh Shafayat, Fahim Tajwar, Ruslan Salakhutdinov, Jeff G. Schneider, Andrea Zanette
2025	J	`jnl`	Multi-Timescale Dynamics Model Bayesian Optimization for Plasma Stabilization in Tokamaks. CoRR Rohit Sonker, Alexandre Capone, Andrew Rothstein, Hiro Josep Farre Kaga, Egemen Kolemen, Jeff G. Schneider
2025	J	`jnl`	State Combinatorial Generalization In Decision Making With Conditional Diffusion Models. CoRR Xintong Duan, Yutong He, Fahim Tajwar, Wentse Chen, Ruslan Salakhutdinov, Jeff G. Schneider
2025	J	`jnl`	State Combinatorial Generalization In Decision Making With Conditional Diffusion Models. Trans. Mach. Learn. Res. Xintong Duan, Yutong He, Fahim Tajwar, Wentse Chen, Ruslan Salakhutdinov, Jeff G. Schneider
2024	J	`jnl`	Assigning Credit with Partial Reward Decoupling in Multi-Agent Proximal Policy Optimization. CoRR Aditya Kapoor, Benjamin Freed, Howie Choset, Jeff G. Schneider
2024	J	`jnl`	Beyond Parameter Count: Implicit Bias in Soft Mixture of Experts. CoRR Youngseog Chung, Dhruv Malik, Jeff G. Schneider, Yuanzhi Li, Aarti Singh
2024	A*	`conf`	Decentralized Multi-Agent Active Search and Tracking when Targets Outnumber Agents. ICRA Arundhati Banerjee, Jeff G. Schneider
2024	A*	`conf`	Diffusion-ES: Gradient-Free Planning with Diffusion for Autonomous and Instruction-Guided Driving. CVPR Brian Yang, Huangyuan Su, Nikolaos Gkanatsios, Tsung-Wei Ke, Ayush Jain, Jeff G. Schneider, Katerina Fragkiadaki
2024	J	`jnl`	Full Shot Predictions for the DIII-D Tokamak via Deep Recurrent Networks. CoRR Ian Char, Youngseog Chung, Joseph Abbate, Egemen Kolemen, Jeff G. Schneider
2024	Misc	`conf`	Genetic Algorithm for Curriculum Design in Multi-Agent Reinforcement Learning. CoRL Yeeho Song, Jeff G. Schneider
2024	J	`jnl`	Measure Preserving Flows for Ergodic Search in Convoluted Environments. CoRR Albert Xu, Bhaskar Vundurthy, Geordan Gutow, Ian Abraham, Jeff G. Schneider, Howie Choset
2024	A*	`conf`	Tractable Joint Prediction and Planning over Discrete Behavior Modes for Urban Driving. ICRA Adam Villaflor, Brian Yang, Huangyuan Su, Katerina Fragkiadaki, John M. Dolan, Jeff G. Schneider
2024	J	`jnl`	What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions. CoRR Sang Keun Choe, Hwijeen Ahn, Juhan Bae, Kewen Zhao, Minsoo Kang, Youngseog Chung, Adithya Pratapa, Willie Neiswanger, Emma Strubell, Teruko Mitamura, Jeff G. Schneider, Eduard H. Hovy, Roger B. Grosse, Eric P. Xing
2023	A*	`conf`	GUTS: Generalized Uncertainty-Aware Thompson Sampling for Multi-Agent Active Search. ICRA Nikhil Angad Bakshi, Tejus Gupta, Ramina Ghods, Jeff G. Schneider
2023	A*	`conf`	Multi-Agent Active Search using Detection and Location Uncertainty. ICRA Arundhati Banerjee, Ramina Ghods, Jeff G. Schneider
2023	A*	`conf`	Multi-Alpha Soft Actor-Critic: Overcoming Stochastic Biases in Maximum Entropy Reinforcement Learning. ICRA Conor Igoe, Swapnil Pande, Siddarth Venkatraman, Jeff G. Schneider
2023	—	`conf`	Offline Model-Based Reinforcement Learning for Tokamak Control. L4DC Ian Char, Joseph Abbate, Laszlo Bardoczi, Mark D. Boyer, Youngseog Chung, Rory Conlin, Keith Erickson, Viraj Mehta, Nathan Richner, Egemen Kolemen, Jeff G. Schneider
2023	J	`jnl`	PID-Inspired Inductive Biases for Deep Reinforcement Learning in Partially Observable Control Tasks. CoRR Ian Char, Jeff G. Schneider
2023	J	`jnl`	Reasoning with Latent Diffusion in Offline Reinforcement Learning. CoRR Siddarth Venkatraman, Shivesh Khaitan, Ravi Tej Akella, John M. Dolan, Jeff G. Schneider, Glen Berseth
2023	J	`jnl`	Sample Efficient Reinforcement Learning from Human Feedback via Active Exploration. CoRR Viraj Mehta, Vikramjeet Das, Ojash Neopane, Yijia Dai, Ilija Bogunovic, Jeff G. Schneider, Willie Neiswanger
2022	J	`jnl`	Learning Cooperative Multi-Agent Policies With Partial Reward Decoupling. IEEE Robotics Autom. Lett. Benjamin Freed, Aditya Kapoor, Ian Abraham, Jeff G. Schneider, Howie Choset
2021	J	`jnl`	Learning Cooperative Multi-Agent Policies with Partial Reward Decoupling. CoRR Benjamin Freed, Aditya Kapoor, Ian Abraham, Jeff G. Schneider, Howie Choset
2021	—	`conf`	Neural Dynamical Systems: Balancing Structure and Flexibility in Physical Prediction. CDC Viraj Mehta, Ian Char, Willie Neiswanger, Youngseog Chung, Andrew Oakleigh Nelson, Mark D. Boyer, Egemen Kolemen, Jeff G. Schneider
2019	J	`jnl`	Multi-fidelity Gaussian Process Bandit Optimisation. J. Artif. Intell. Res. Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos
2017	A	`conf`	Active Optimization and Self Driving Cars. AAMAS Jeff G. Schneider
2017	A*	`conf`	Active Search for Sparse Signals with Region Sensing. AAAI Yifei Ma, Roman Garnett, Jeff G. Schneider
2017	J	`jnl`	Asynchronous Parallel Bayesian Optimisation via Thompson Sampling. CoRR Kirthevasan Kandasamy, Akshay Krishnamurthy, Jeff G. Schneider, Barnabás Póczos
2017	—	`conf`	Deep Learning with Sets and Point Clouds. ICLR (Workshop) Siamak Ravanbakhsh, Jeff G. Schneider, Barnabás Póczos
2017	A*	`conf`	Enabling Dark Energy Science with Deep Generative Models of Galaxy Images. AAAI Siamak Ravanbakhsh, François Lanusse, Rachel Mandelbaum, Jeff G. Schneider, Barnabás Póczos
2017	A*	`conf`	Equivariance Through Parameter-Sharing. ICML Siamak Ravanbakhsh, Jeff G. Schneider, Barnabás Póczos
2017	J	`jnl`	Equivariance Through Parameter-Sharing. CoRR Siamak Ravanbakhsh, Jeff G. Schneider, Barnabás Póczos
2017	J	`jnl`	Estimating Cosmological Parameters from the Dark Matter Distribution. CoRR Siamak Ravanbakhsh, Junier B. Oliva, Sebastian Fromenteau, Layne C. Price, Shirley Ho, Jeff G. Schneider, Barnabás Póczos
2017	A*	`conf`	Multi-fidelity Bayesian Optimisation with Continuous Approximations. ICML Kirthevasan Kandasamy, Gautam Dasarathy, Jeff G. Schneider, Barnabás Póczos
2017	J	`jnl`	Query efficient posterior estimation in scientific experiments via Bayesian active learning. Artif. Intell. Kirthevasan Kandasamy, Jeff G. Schneider, Barnabás Póczos
2017	J	`jnl`	Recurrent Estimation of Distributions. CoRR Junier B. Oliva, Kumar Avinava Dubey, Barnabás Póczos, Eric P. Xing, Jeff G. Schneider
2017	A*	`conf`	The Statistical Recurrent Unit. ICML Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider
2017	J	`jnl`	The Statistical Recurrent Unit. CoRR Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider
2016	J	`jnl`	Active Search for Sparse Signals with Region Sensing. CoRR Yifei Ma, Roman Garnett, Jeff G. Schneider
2016	A	`conf`	Bayesian Nonparametric Kernel-Learning. AISTATS Junier B. Oliva, Avinava Dubey, Andrew Gordon Wilson, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing
2016	J	`jnl`	Deep Learning with Sets and Point Clouds. CoRR Siamak Ravanbakhsh, Jeff G. Schneider, Barnabás Póczos
2016	J	`jnl`	Enabling Dark Energy Science with Deep Generative Models of Galaxy Images. CoRR Siamak Ravanbakhsh, François Lanusse, Rachel Mandelbaum, Jeff G. Schneider, Barnabás Póczos
2016	A*	`conf`	Estimating Cosmological Parameters from the Dark Matter Distribution. ICML Siamak Ravanbakhsh, Junier B. Oliva, Sebastian Fromenteau, Layne Price, Shirley Ho, Jeff G. Schneider, Barnabás Póczos
2016	—	`conf`	Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations. NIPS Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos
2016	A	`conf`	High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models. AISTATS Chun-Liang Li, Kirthevasan Kandasamy, Barnabás Póczos, Jeff G. Schneider
2016	A*	`conf`	Linear-Time Learning on Distributions with Approximate Kernel Embeddings. AAAI Danica J. Sutherland, Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider
2016	J	`jnl`	Multi-fidelity Gaussian Process Bandit Optimisation. CoRR Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos
2016	A*	`conf`	Nonparametric Risk and Stability Analysis for Multi-Task Learning Problems. IJCAI Xuezhi Wang, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos
2016	A	`conf`	Stochastic Neural Networks with Monotonic Activation Functions. AISTATS Siamak Ravanbakhsh, Barnabás Póczos, Jeff G. Schneider, Dale Schuurmans, Russell Greiner
2016	J	`jnl`	Stochastic Neural Networks with Monotonic Activation Functions. CoRR Siamak Ravanbakhsh, Barnabás Póczos, Jeff G. Schneider, Dale Schuurmans, Russell Greiner
2016	—	`conf`	The Multi-fidelity Multi-armed Bandit. NIPS Kirthevasan Kandasamy, Gautam Dasarathy, Barnabás Póczos, Jeff G. Schneider
2016	J	`jnl`	The Multi-fidelity Multi-armed Bandit. CoRR Kirthevasan Kandasamy, Gautam Dasarathy, Jeff G. Schneider, Barnabás Póczos
2015	A	`conf`	Active Pointillistic Pattern Search. AISTATS Yifei Ma, Danica J. Sutherland, Roman Garnett, Jeff G. Schneider
2015	A	`conf`	Active Search and Bandits on Graphs using Sigma-Optimality. UAI Yifei Ma, Tzu-Kuo Huang, Jeff G. Schneider
2015	A*	`conf`	Bayesian Active Learning for Posterior Estimation - IJCAI-15 Distinguished Paper. IJCAI Kirthevasan Kandasamy, Jeff G. Schneider, Barnabás Póczos
2015	J	`jnl`	Deep Mean Maps. CoRR Junier B. Oliva, Danica J. Sutherland, Barnabás Póczos, Jeff G. Schneider
2015	A	`conf`	Fast Function to Function Regression. AISTATS Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Eric P. Xing, Hy Trac, Shirley Ho, Jeff G. Schneider
2015	A*	`conf`	Finding Galaxies in the Shadows of Quasars with Gaussian Processes. ICML Roman Garnett, Shirley Ho, Jeff G. Schneider
2015	A	`conf`	Generalization Bounds for Transfer Learning under Model Shift. UAI Xuezhi Wang, Jeff G. Schneider
2015	A*	`conf`	High Dimensional Bayesian Optimisation and Bandits via Additive Models. ICML Kirthevasan Kandasamy, Jeff G. Schneider, Barnabás Póczos
2015	J	`jnl`	High Dimensional Bayesian Optimisation and Bandits via Additive Models. CoRR Kirthevasan Kandasamy, Jeff G. Schneider, Barnabás Póczos
2015	J	`jnl`	Linear-time Learning on Distributions with Approximate Kernel Embeddings. CoRR Danica J. Sutherland, Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider
2015	A	`conf`	On the Error of Random Fourier Features. UAI Danica J. Sutherland, Jeff G. Schneider
2015	J	`jnl`	On the Error of Random Fourier Features. CoRR Danica J. Sutherland, Jeff G. Schneider
2015	A	`conf`	Statistical Learning in Chip (SLIC). ICCAD Ronald D. Blanton, Xin Li, Ken Mai, Diana Marculescu, Radu Marculescu, Jeyanandh Paramesh, Jeff G. Schneider, Donald E. Thomas
2014	A	`conf`	Active Area Search via Bayesian Quadrature. AISTATS Yifei Ma, Roman Garnett, Jeff G. Schneider
2014	A*	`conf`	Active Transfer Learning under Model Shift. ICML Xuezhi Wang, Tzu-Kuo Huang, Jeff G. Schneider
2014	A	`conf`	Fast Distribution To Real Regression. AISTATS Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing
2014	J	`jnl`	Fast Function to Function Regression. CoRR Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Eric P. Xing, Jeff G. Schneider
2014	—	`conf`	Flexible Transfer Learning under Support and Model Shift. NIPS Xuezhi Wang, Jeff G. Schneider
2014	A	`conf`	FuSSO: Functional Shrinkage and Selection Operator. AISTATS Junier B. Oliva, Barnabás Póczos, Timothy D. Verstynen, Aarti Singh, Jeff G. Schneider, Fang-Cheng Yeh, Wen-Yih Isaac Tseng
2014	A	`conf`	Learning from Point Sets with Observational Bias. UAI Liang Xiong, Jeff G. Schneider
2014	—	`conf`	SLIC: Statistical learning in chip. ISIC Ronald D. Blanton, Xin Li, Ken Mai, Diana Marculescu, Radu Marculescu, Jeyanandh Paramesh, Jeff G. Schneider, Donald E. Thomas
2014	B	`conf`	Systematic Labeling Bias: De-biasing Where Everyone is Wrong. ICPR Guillermo F. Cabrera, Christopher J. Miller, Jeff G. Schneider
2013	A*	`conf`	Active learning and search on low-rank matrices. KDD Danica J. Sutherland, Barnabás Póczos, Jeff G. Schneider
2013	A*	`conf`	Active search on graphs. KDD Xuezhi Wang, Roman Garnett, Jeff G. Schneider
2013	—	`conf`	Distribution to Distribution Regression. ICML (3) Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider
2013	A*	`conf`	Efficient Learning on Point Sets. ICDM Liang Xiong, Barnabás Póczos, Jeff G. Schneider
2013	—	`conf`	Expensive Function Optimization with Stochastic Binary Outcomes. ICML (3) Matthew Tesch, Jeff G. Schneider, Howie Choset
2013	A*	`conf`	Expensive multiobjective optimization for robotics. ICRA Matthew Tesch, Jeff G. Schneider, Howie Choset
2013	J	`jnl`	Fast Distribution To Real Regression. CoRR Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing
2013	J	`jnl`	FuSSO: Functional Shrinkage and Selection Operator. CoRR Junier B. Oliva, Barnabás Póczos, Timothy D. Verstynen, Aarti Singh, Jeff G. Schneider, Fang-Cheng Yeh, Wen-Yih Isaac Tseng
2013	—	`conf`	Learning Hidden Markov Models from Non-sequence Data via Tensor Decomposition. NIPS Tzu-Kuo Huang, Jeff G. Schneider
2013	J	`jnl`	Real-valued All-Dimensions search: Low-overhead rapid searching over subsets of attributes CoRR Andrew W. Moore, Jeff G. Schneider
2013	—	`conf`	Spectral Learning of Hidden Markov Models from Dynamic and Static Data. ICML (3) Tzu-Kuo Huang, Jeff G. Schneider
2013	—	`conf`	Σ-Optimality for Active Learning on Gaussian Random Fields. NIPS Yifei Ma, Roman Garnett, Jeff G. Schneider
2012	A	`conf`	A Composite Likelihood View for Multi-Label Classification. AISTATS Yi Zhang, Jeff G. Schneider
2012	A*	`conf`	Bayesian Optimal Active Search and Surveying. ICML Roman Garnett, Yamuna Krishnamurthy, Xuehan Xiong, Jeff G. Schneider, Richard P. Mann
2012	J	`jnl`	Copula-based Kernel Dependency Measures CoRR Barnabás Póczos, Zoubin Ghahramani, Jeff G. Schneider
2012	A*	`conf`	Copula-based Kernel Dependency Measures. ICML Barnabás Póczos, Zoubin Ghahramani, Jeff G. Schneider
2012	—	`conf`	Learning Bi-clustered Vector Autoregressive Models. ECML/PKDD (2) Tzu-Kuo Huang, Jeff G. Schneider
2012	A*	`conf`	Maximum Margin Output Coding. ICML Yi Zhang, Jeff G. Schneider
2012	J	`jnl`	Nonparametric Divergence Estimation with Applications to Machine Learning on Distributions CoRR Barnabás Póczos, Liang Xiong, Jeff G. Schneider
2012	A	`conf`	Nonparametric Estimation of Conditional Information and Divergences. AISTATS Barnabás Póczos, Jeff G. Schneider
2012	A*	`conf`	Nonparametric kernel estimators for image classification. CVPR Barnabás Póczos, Liang Xiong, Danica J. Sutherland, Jeff G. Schneider
2012	J	`jnl`	Protein subcellular location pattern classification in cellular images using latent discriminative models. Bioinform. Jieyue Li, Liang Xiong, Jeff G. Schneider, Robert F. Murphy
2012	J	`jnl`	Submodularity in Batch Active Learning and Survey Problems on Gaussian Random Fields CoRR Yifei Ma, Roman Garnett, Jeff G. Schneider
2012	J	`jnl`	Support Distribution Machines CoRR Barnabás Póczos, Liang Xiong, Danica J. Sutherland, Jeff G. Schneider
2011	A	`conf`	Adapting control policies for expensive systems to changing environments. IROS Matthew Tesch, Jeff G. Schneider, Howie Choset
2011	A*	`conf`	Direct Robust Matrix Factorizatoin for Anomaly Detection. ICDM Liang Xiong, Xi Chen, Jeff G. Schneider
2011	—	`conf`	Group Anomaly Detection using Flexible Genre Models. NIPS Liang Xiong, Barnabás Póczos, Jeff G. Schneider
2011	A	`conf`	Hierarchical Probabilistic Models for Group Anomaly Detection. AISTATS Liang Xiong, Barnabás Póczos, Jeff G. Schneider, Andrew J. Connolly, Jake VanderPlas
2011	—	`conf`	Learning Auto-regressive Models from Sequence and Non-sequence Data. NIPS Tzu-Kuo Huang, Jeff G. Schneider
2011	A	`conf`	Multi-Label Output Codes using Canonical Correlation Analysis. AISTATS Yi Zhang, Jeff G. Schneider
2011	A	`conf`	Nonparametric Divergence Estimation with Applications to Machine Learning on Distributions. UAI Barnabás Póczos, Liang Xiong, Jeff G. Schneider
2011	—	`conf`	Nonparametric divergence estimators for independent subspace analysis. EUSIPCO Barnabás Póczos, Zoltán Szabó, Jeff G. Schneider
2011	A	`conf`	On the Estimation of alpha-Divergences. AISTATS Barnabás Póczos, Jeff G. Schneider
2011	A	`conf`	Using response surfaces and expected improvement to optimize snake robot gait parameters. IROS Matthew Tesch, Jeff G. Schneider, Howie Choset
2010	A	`conf`	A Probabilistic Framework to Learn from Multiple Annotators with Time-Varying Accuracy. SDM Pinar Donmez, Jaime G. Carbonell, Jeff G. Schneider
2010	A	`conf`	Learning Compressible Models. SDM Yi Zhang, Jeff G. Schneider, Artur Dubrawski
2010	—	`conf`	Learning Multiple Tasks with a Sparse Matrix-Normal Penalty. NIPS Yi Zhang, Jeff G. Schneider
2010	A	`conf`	Learning Nonlinear Dynamic Models from Non-sequenced Data. AISTATS Tzu-Kuo Huang, Le Song, Jeff G. Schneider
2010	A*	`conf`	Projection Penalties: Dimension Reduction without Loss. ICML Yi Zhang, Jeff G. Schneider
2010	A	`conf`	Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization. SDM Liang Xiong, Xi Chen, Tzu-Kuo Huang, Jeff G. Schneider, Jaime G. Carbonell
2009	A*	`conf`	Efficiently learning the accuracy of labeling sources for selective sampling. KDD Pinar Donmez, Jaime G. Carbonell, Jeff G. Schneider
2009	A*	`conf`	Learning linear dynamical systems without sequence information. ICML Tzu-Kuo Huang, Jeff G. Schneider
2008	A*	`conf`	Actively learning level-sets of composite functions. ICML Brent Bryan, Jeff G. Schneider
2008	A*	`conf`	Anomaly pattern detection in categorical datasets. KDD Kaustav Das, Jeff G. Schneider, Daniel B. Neill
2008	Misc	`conf`	Learning Detectors of Events in Multivariate Time Series. AMIA Josep Roure, Artur Dubrawski, Jeff G. Schneider
2008	—	`conf`	Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled Text. NIPS Yi Zhang, Jeff G. Schneider, Artur Dubrawski
2007	—	`conf`	A Study into Detection of Bio-Events in Multiple Streams of Surveillance Data. BioSurveillance Josep Roure, Artur Dubrawski, Jeff G. Schneider
2007	A*	`conf`	Detecting anomalous records in categorical datasets. KDD Kaustav Das, Jeff G. Schneider
2007	A*	`conf`	Efficiently computing minimax expected-size confidence regions. ICML Brent Bryan, H. Brendan McMahan, Chad M. Schafer, Jeff G. Schneider
2005	—	`conf`	Active Learning For Identifying Function Threshold Boundaries. NIPS Brent Bryan, Jeff G. Schneider, Robert Nichol, Christopher J. Miller, Christopher R. Genovese, Larry A. Wasserman
2005	A*	`conf`	Game Theoretic Control for Robot Teams. ICRA Rosemary Emery-Montemerlo, Geoffrey J. Gordon, Jeff G. Schneider, Sebastian Thrun
2005	A*	`conf`	Learning Opportunity Costs in Multi-Robot Market Based Planners. ICRA Jeff G. Schneider, David Apfelbaum, Drew Bagnell, Reid G. Simmons
2004	A	`conf`	Approximate Solutions for Partially Observable Stochastic Games with Common Payoffs. AAMAS Rosemary Emery-Montemerlo, Geoffrey J. Gordon, Jeff G. Schneider, Sebastian Thrun
2004	J	`jnl`	Automatic Construction of Active Appearance Models as an Image Coding Problem. IEEE Trans. Pattern Anal. Mach. Intell. Simon Baker, Iain A. Matthews, Jeff G. Schneider
2004	A*	`conf`	Belief state approaches to signaling alarms in surveillance systems. KDD Kaustav Das, Andrew W. Moore, Jeff G. Schneider
2003	A*	`conf`	Covariant Policy Search. IJCAI J. Andrew Bagnell, Jeff G. Schneider
2003	A*	`conf`	Finding Underlying Connections: A Fast Graph-Based Method for Link Analysis and Collaboration Queries. ICML Jeremy Kubica, Andrew W. Moore, David Cohn, Jeff G. Schneider
2003	—	`conf`	Policy Search by Dynamic Programming. NIPS J. Andrew Bagnell, Sham M. Kakade, Andrew Y. Ng, Jeff G. Schneider
2003	A*	`conf`	Tractable Group Detection on Large Link Data Sets. ICDM Jeremy Kubica, Andrew W. Moore, Jeff G. Schneider
2002	A	`conf`	Real-valued All-Dimensions Search: Low-overhead Rapid Searching over Subsets of Attributes. UAI Andrew W. Moore, Jeff G. Schneider
2002	—	`conf`	Stochastic Link and Group Detection. AAAI/IAAI Jeremy Kubica, Andrew W. Moore, Jeff G. Schneider, Yiming Yang
2001	A*	`conf`	Autonomous Helicopter Control using Reinforcement Learning Policy Search Methods. ICRA J. Andrew Bagnell, Jeff G. Schneider
2001	A	`conf`	Classification-Driven Pathological Neuroimage Retrieval Using Statistical Asymmetry Measures. MICCAI Yanxi Liu, Frank Dellaert, William E. Rothfus, Andrew W. Moore, Jeff G. Schneider, Takeo Kanade
2000	A*	`conf`	Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions. ICRA Andrew W. Moore, Jeff G. Schneider, Justin A. Boyan, Mary S. Lee
2000	—	`conf`	Reinforcement Learning for Cooperating and Communicating Reactive Agents in Electrical Power Grids. Balancing Reactivity and Social Deliberation in Multi-Agent Systems Martin A. Riedmiller, Andrew W. Moore, Jeff G. Schneider
1999	A	`conf`	3-D Deformable Registration of Medical Images Using a Statistical Atlas. MICCAI Mei Chen, Takeo Kanade, Dean Pomerleau, Jeff G. Schneider
1999	A*	`conf`	Distributed Value Functions. ICML Jeff G. Schneider, Weng-Keen Wong, Andrew W. Moore, Martin A. Riedmiller
1998	A*	`conf`	Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions. ICML Andrew W. Moore, Jeff G. Schneider, Justin A. Boyan, Mary S. Lee
1998	A*	`conf`	Value Function Based Production Scheduling. ICML Jeff G. Schneider, Justin A. Boyan, Andrew W. Moore
1997	A*	`conf`	Efficient Locally Weighted Polynomial Regression Predictions. ICML Andrew W. Moore, Jeff G. Schneider, Kan Deng
1996	—	`conf`	Exploiting Model Uncertainty Estimates for Safe Dynamic Control Learning. NIPS Jeff G. Schneider
1995	—	`conf`	Cooperative coaching in robot learning. IROS (3) Jeff G. Schneider, Christopher M. Brown
1995	—	`conf`	Memory-based Stochastic Optimization. NIPS Andrew W. Moore, Jeff G. Schneider
1994	A	`conf`	Efficient search for robot skill learning: simulation and reality. IROS Jeff G. Schneider, Roger F. Gans
1994	A*	`conf`	High Dimension Action Spaces in Robot Skill Learning. AAAI Jeff G. Schneider
1993	—	`conf`	Robot Skill Learning, Basic Functions, and Control Regimes. ICRA (1) Jeff G. Schneider, Christopher M. Brown