Schneider, Jeff G.

48 publications

NeurIPS 2023 PID-Inspired Inductive Biases for Deep Reinforcement Learning in Partially Observable Control Tasks Ian Char, Jeff G. Schneider

NeurIPS 2022 Exploration via Planning for Information About the Optimal Trajectory Viraj Mehta, Ian Char, Joseph Abbate, Rory Conlin, Mark Boyer, Stefano Ermon, Jeff G. Schneider, Willie Neiswanger

NeurIPS 2021 Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification Youngseog Chung, Willie Neiswanger, Ian Char, Jeff G. Schneider

JAIR 2019 Multi-Fidelity Gaussian Process Bandit Optimisation Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos

AAAI 2017 Active Search for Sparse Signals with Region Sensing Yifei Ma, Roman Garnett, Jeff G. Schneider

ICLR 2017 Deep Learning with Sets and Point Clouds Siamak Ravanbakhsh, Jeff G. Schneider, Barnabás Póczos

AAAI 2017 Enabling Dark Energy Science with Deep Generative Models of Galaxy Images Siamak Ravanbakhsh, François Lanusse, Rachel Mandelbaum, Jeff G. Schneider, Barnabás Póczos

AISTATS 2016 Bayesian Nonparametric Kernel-Learning Junier B. Oliva, Avinava Dubey, Andrew Gordon Wilson, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing

AISTATS 2016 High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models Chun-Liang Li, Kirthevasan Kandasamy, Barnabás Póczos, Jeff G. Schneider

AAAI 2016 Linear-Time Learning on Distributions with Approximate Kernel Embeddings Danica J. Sutherland, Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider

IJCAI 2016 Nonparametric Risk and Stability Analysis for Multi-Task Learning Problems Xuezhi Wang, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos

AISTATS 2016 Stochastic Neural Networks with Monotonic Activation Functions Siamak Ravanbakhsh, Barnabás Póczos, Jeff G. Schneider, Dale Schuurmans, Russell Greiner

AISTATS 2015 Active Pointillistic Pattern Search Yifei Ma, Danica J. Sutherland, Roman Garnett, Jeff G. Schneider

UAI 2015 Active Search and Bandits on Graphs Using Sigma-Optimality Yifei Ma, Tzu-Kuo Huang, Jeff G. Schneider

IJCAI 2015 Bayesian Active Learning for Posterior Estimation - IJCAI-15 Distinguished Paper Kirthevasan Kandasamy, Jeff G. Schneider, Barnabás Póczos

AISTATS 2015 Fast Function to Function Regression Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Eric P. Xing, Hy Trac, Shirley Ho, Jeff G. Schneider

UAI 2015 Generalization Bounds for Transfer Learning Under Model Shift Xuezhi Wang, Jeff G. Schneider

UAI 2015 On the Error of Random Fourier Features Danica J. Sutherland, Jeff G. Schneider

AISTATS 2014 Active Area Search via Bayesian Quadrature Yifei Ma, Roman Garnett, Jeff G. Schneider

AISTATS 2014 Fast Distribution to Real Regression Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing

AISTATS 2014 FuSSO: Functional Shrinkage and Selection Operator Junier B. Oliva, Barnabás Póczos, Timothy D. Verstynen, Aarti Singh, Jeff G. Schneider, Fang-Cheng Yeh, Wen-Yih Isaac Tseng

UAI 2014 Learning from Point Sets with Observational Bias Liang Xiong, Jeff G. Schneider

ICML 2012 Bayesian Optimal Active Search and Surveying Roman Garnett, Yamuna Krishnamurthy, Xuehan Xiong, Jeff G. Schneider, Richard P. Mann

ICML 2012 Copula-Based Kernel Dependency Measures Barnabás Póczos, Zoubin Ghahramani, Jeff G. Schneider

ECML-PKDD 2012 Learning Bi-Clustered Vector Autoregressive Models Tzu-Kuo Huang, Jeff G. Schneider

ICML 2012 Maximum Margin Output Coding Yi Zhang, Jeff G. Schneider

CVPR 2012 Nonparametric Kernel Estimators for Image Classification Barnabás Póczos, Liang Xiong, Danica J. Sutherland, Jeff G. Schneider

NeurIPS 2011 Group Anomaly Detection Using Flexible Genre Models Liang Xiong, Barnabás Póczos, Jeff G. Schneider

NeurIPS 2011 Learning Auto-Regressive Models from Sequence and Non-Sequence Data Tzu-kuo Huang, Jeff G. Schneider

UAI 2011 Nonparametric Divergence Estimation with Applications to Machine Learning on Distributions Barnabás Póczos, Liang Xiong, Jeff G. Schneider

NeurIPS 2010 Learning Multiple Tasks with a Sparse Matrix-Normal Penalty Yi Zhang, Jeff G. Schneider

ICML 2010 Projection Penalties: Dimension Reduction Without Loss Yi Zhang, Jeff G. Schneider

ICML 2009 Learning Linear Dynamical Systems Without Sequence Information Tzu-Kuo Huang, Jeff G. Schneider

ICML 2008 Actively Learning Level-Sets of Composite Functions Brent Bryan, Jeff G. Schneider

NeurIPS 2008 Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled Text Yi Zhang, Artur Dubrawski, Jeff G. Schneider

ICML 2007 Efficiently Computing Minimax Expected-Size Confidence Regions Brent Bryan, H. Brendan McMahan, Chad M. Schafer, Jeff G. Schneider

IJCAI 2003 Covariant Policy Search J. Andrew Bagnell, Jeff G. Schneider

ICML 2003 Finding Underlying Connections: A Fast Graph-Based Method for Link Analysis and Collaboration Queries Jeremy Kubica, Andrew W. Moore, David Cohn, Jeff G. Schneider

NeurIPS 2003 Policy Search by Dynamic Programming J. A. Bagnell, Sham M. Kakade, Jeff G. Schneider, Andrew Y. Ng

UAI 2002 Real-Valued All-Dimensions Search: Low-Overhead Rapid Searching over Subsets of Attributes Andrew W. Moore, Jeff G. Schneider

AAAI 2002 Stochastic Link and Group Detection Jeremy Kubica, Andrew W. Moore, Jeff G. Schneider, Yiming Yang

ICML 1999 Distributed Value Functions Jeff G. Schneider, Weng-Keen Wong, Andrew W. Moore, Martin A. Riedmiller

ICML 1998 Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions Andrew W. Moore, Jeff G. Schneider, Justin A. Boyan, Mary S. Lee

ICML 1998 Value Function Based Production Scheduling Jeff G. Schneider, Justin A. Boyan, Andrew W. Moore

ICML 1997 Efficient Locally Weighted Polynomial Regression Predictions Andrew W. Moore, Jeff G. Schneider, Kan Deng

NeurIPS 1996 Exploiting Model Uncertainty Estimates for Safe Dynamic Control Learning Jeff G. Schneider

NeurIPS 1995 Memory-Based Stochastic Optimization Andrew W. Moore, Jeff G. Schneider

AAAI 1994 High Dimension Action Spaces in Robot Skill Learning Jeff G. Schneider