Jeff G. Schneider

ORCID

Publication Activity (10 Years)

Years Active: 1993-2024
Publications (10 Years): 55

Top Venues

Publications

Arundhati Banerjee, Jeff G. Schneider
Decentralized Multi-Agent Active Search and Tracking when Targets Outnumber Agents. ICRA (2024)
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
What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions. CoRR (2024)
Ian Char, Youngseog Chung, Joseph Abbate, Egemen Kolemen, Jeff G. Schneider
Full Shot Predictions for the DIII-D Tokamak via Deep Recurrent Networks. CoRR (2024)
Adam Villaflor, Brian Yang, Huangyuan Su, Katerina Fragkiadaki, John Dolan, Jeff G. Schneider
Tractable Joint Prediction and Planning over Discrete Behavior Modes for Urban Driving. ICRA (2024)
Nikhil Angad Bakshi, Tejus Gupta, Ramina Ghods, Jeff G. Schneider
GUTS: Generalized Uncertainty-Aware Thompson Sampling for Multi-Agent Active Search. ICRA (2023)
Ian Char, Joseph Abbate, Laszlo Bardoczi, Mark D. Boyer, Youngseog Chung, Rory Conlin, Keith Erickson, Viraj Mehta, Nathan Richner, Egemen Kolemen, Jeff G. Schneider
Offline Model-Based Reinforcement Learning for Tokamak Control. L4DC (2023)
Viraj Mehta, Vikramjeet Das, Ojash Neopane, Yijia Dai, Ilija Bogunovic, Jeff G. Schneider, Willie Neiswanger
Sample Efficient Reinforcement Learning from Human Feedback via Active Exploration. CoRR (2023)
Ian Char, Jeff G. Schneider
PID-Inspired Inductive Biases for Deep Reinforcement Learning in Partially Observable Control Tasks. CoRR (2023)
Arundhati Banerjee, Ramina Ghods, Jeff G. Schneider
Multi-Agent Active Search using Detection and Location Uncertainty. ICRA (2023)
Conor Igoe, Swapnil Pande, Siddarth Venkatraman, Jeff G. Schneider
Multi-Alpha Soft Actor-Critic: Overcoming Stochastic Biases in Maximum Entropy Reinforcement Learning. ICRA (2023)
Siddarth Venkatraman, Shivesh Khaitan, Ravi Tej Akella, John M. Dolan, Jeff G. Schneider, Glen Berseth
Reasoning with Latent Diffusion in Offline Reinforcement Learning. CoRR (2023)
Benjamin Freed, Aditya Kapoor, Ian Abraham, Jeff G. Schneider, Howie Choset
Learning Cooperative Multi-Agent Policies With Partial Reward Decoupling. IEEE Robotics Autom. Lett. 7 (2) (2022)
Viraj Mehta, Ian Char, Willie Neiswanger, Youngseog Chung, Andrew Oakleigh Nelson, Mark D. Boyer, Egemen Kolemen, Jeff G. Schneider
Neural Dynamical Systems: Balancing Structure and Flexibility in Physical Prediction. CDC (2021)
Benjamin Freed, Aditya Kapoor, Ian Abraham, Jeff G. Schneider, Howie Choset
Learning Cooperative Multi-Agent Policies with Partial Reward Decoupling. CoRR (2021)
Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos
Multi-fidelity Gaussian Process Bandit Optimisation. J. Artif. Intell. Res. 66 (2019)
Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider
The Statistical Recurrent Unit. ICML (2017)
Siamak Ravanbakhsh, Jeff G. Schneider, Barnabás Póczos
Deep Learning with Sets and Point Clouds. ICLR (Workshop) (2017)
Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider
The Statistical Recurrent Unit. CoRR (2017)
Siamak Ravanbakhsh, Jeff G. Schneider, Barnabás Póczos
Equivariance Through Parameter-Sharing. CoRR (2017)
Siamak Ravanbakhsh, Jeff G. Schneider, Barnabás Póczos
Equivariance Through Parameter-Sharing. ICML (2017)
Jeff G. Schneider
Active Optimization and Self Driving Cars. AAMAS (2017)
Kirthevasan Kandasamy, Gautam Dasarathy, Jeff G. Schneider, Barnabás Póczos
Multi-fidelity Bayesian Optimisation with Continuous Approximations. ICML (2017)
Siamak Ravanbakhsh, Junier B. Oliva, Sebastian Fromenteau, Layne C. Price, Shirley Ho, Jeff G. Schneider, Barnabás Póczos
Estimating Cosmological Parameters from the Dark Matter Distribution. CoRR (2017)
Siamak Ravanbakhsh, Francois Lanusse, Rachel Mandelbaum, Jeff G. Schneider, Barnabás Póczos
Enabling Dark Energy Science with Deep Generative Models of Galaxy Images. AAAI (2017)
Kirthevasan Kandasamy, Akshay Krishnamurthy, Jeff G. Schneider, Barnabás Póczos
Asynchronous Parallel Bayesian Optimisation via Thompson Sampling. CoRR (2017)
Kirthevasan Kandasamy, Jeff G. Schneider, Barnabás Póczos
Query efficient posterior estimation in scientific experiments via Bayesian active learning. Artif. Intell. 243 (2017)
Yifei Ma, Roman Garnett, Jeff G. Schneider
Active Search for Sparse Signals with Region Sensing. AAAI (2017)
Junier B. Oliva, Kumar Avinava Dubey, Barnabás Póczos, Eric P. Xing, Jeff G. Schneider
Recurrent Estimation of Distributions. CoRR (2017)
Danica J. Sutherland, Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider
Linear-Time Learning on Distributions with Approximate Kernel Embeddings. AAAI (2016)
Siamak Ravanbakhsh, Francois Lanusse, Rachel Mandelbaum, Jeff G. Schneider, Barnabás Póczos
Enabling Dark Energy Science with Deep Generative Models of Galaxy Images. CoRR (2016)
Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos
Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations. NIPS (2016)
Kirthevasan Kandasamy, Gautam Dasarathy, Jeff G. Schneider, Barnabás Póczos
The Multi-fidelity Multi-armed Bandit. CoRR (2016)
Siamak Ravanbakhsh, Barnabás Póczos, Jeff G. Schneider, Dale Schuurmans, Russell Greiner
Stochastic Neural Networks with Monotonic Activation Functions. CoRR (2016)
Chun-Liang Li, Kirthevasan Kandasamy, Barnabás Póczos, Jeff G. Schneider
High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models. AISTATS (2016)
Siamak Ravanbakhsh, Junier B. Oliva, Sebastian Fromenteau, Layne Price, Shirley Ho, Jeff G. Schneider, Barnabás Póczos
Estimating Cosmological Parameters from the Dark Matter Distribution. ICML (2016)
Yifei Ma, Roman Garnett, Jeff G. Schneider
Active Search for Sparse Signals with Region Sensing. CoRR (2016)
Siamak Ravanbakhsh, Jeff G. Schneider, Barnabás Póczos
Deep Learning with Sets and Point Clouds. CoRR (2016)
Xuezhi Wang, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos
Nonparametric Risk and Stability Analysis for Multi-Task Learning Problems. IJCAI (2016)
Siamak Ravanbakhsh, Barnabás Póczos, Jeff G. Schneider, Dale Schuurmans, Russell Greiner
Stochastic Neural Networks with Monotonic Activation Functions. AISTATS (2016)
Kirthevasan Kandasamy, Gautam Dasarathy, Barnabás Póczos, Jeff G. Schneider
The Multi-fidelity Multi-armed Bandit. NIPS (2016)
Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos
Multi-fidelity Gaussian Process Bandit Optimisation. CoRR (2016)
Junier B. Oliva, Avinava Dubey, Andrew Gordon Wilson, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing
Bayesian Nonparametric Kernel-Learning. AISTATS (2016)
Roman Garnett, Shirley Ho, Jeff G. Schneider
Finding Galaxies in the Shadows of Quasars with Gaussian Processes. ICML (2015)
Danica J. Sutherland, Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider
Linear-time Learning on Distributions with Approximate Kernel Embeddings. CoRR (2015)
Danica J. Sutherland, Jeff G. Schneider
On the Error of Random Fourier Features. UAI (2015)
Kirthevasan Kandasamy, Jeff G. Schneider, Barnabás Póczos
High Dimensional Bayesian Optimisation and Bandits via Additive Models. ICML (2015)
Danica J. Sutherland, Jeff G. Schneider
On the Error of Random Fourier Features. CoRR (2015)
Xuezhi Wang, Jeff G. Schneider
Generalization Bounds for Transfer Learning under Model Shift. UAI (2015)
Yifei Ma, Tzu-Kuo Huang, Jeff G. Schneider
Active Search and Bandits on Graphs using Sigma-Optimality. UAI (2015)
Yifei Ma, Danica J. Sutherland, Roman Garnett, Jeff G. Schneider
Active Pointillistic Pattern Search. AISTATS (2015)
Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Eric P. Xing, Hy Trac, Shirley Ho, Jeff G. Schneider
Fast Function to Function Regression. AISTATS (2015)
Ronald D. Blanton, Xin Li, Ken Mai, Diana Marculescu, Radu Marculescu, Jeyanandh Paramesh, Jeff G. Schneider, Donald E. Thomas
Statistical Learning in Chip (SLIC). ICCAD (2015)
Junier B. Oliva, Danica J. Sutherland, Barnabás Póczos, Jeff G. Schneider
Deep Mean Maps. CoRR (2015)
Kirthevasan Kandasamy, Jeff G. Schneider, Barnabás Póczos
Bayesian Active Learning for Posterior Estimation - IJCAI-15 Distinguished Paper. IJCAI (2015)
Kirthevasan Kandasamy, Jeff G. Schneider, Barnabás Póczos
High Dimensional Bayesian Optimisation and Bandits via Additive Models. CoRR (2015)
Xuezhi Wang, Tzu-Kuo Huang, Jeff G. Schneider
Active Transfer Learning under Model Shift. ICML (2014)
Guillermo F. Cabrera, Christopher J. Miller, Jeff G. Schneider
Systematic Labeling Bias: De-biasing Where Everyone is Wrong. ICPR (2014)
Ronald D. Blanton, Xin Li, Ken Mai, Diana Marculescu, Radu Marculescu, Jeyanandh Paramesh, Jeff G. Schneider, Donald E. Thomas
SLIC: Statistical learning in chip. ISIC (2014)
Liang Xiong, Jeff G. Schneider
Learning from Point Sets with Observational Bias. UAI (2014)
Junier B. Oliva, Barnabás Póczos, Timothy D. Verstynen, Aarti Singh, Jeff G. Schneider, Fang-Cheng Yeh, Wen-Yih Isaac Tseng
FuSSO: Functional Shrinkage and Selection Operator. AISTATS (2014)
Yifei Ma, Roman Garnett, Jeff G. Schneider
Active Area Search via Bayesian Quadrature. AISTATS (2014)
Xuezhi Wang, Jeff G. Schneider
Flexible Transfer Learning under Support and Model Shift. NIPS (2014)
Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Eric P. Xing, Jeff G. Schneider
Fast Function to Function Regression. CoRR (2014)
Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing
Fast Distribution To Real Regression. AISTATS (2014)
Tzu-Kuo Huang, Jeff G. Schneider
Learning Hidden Markov Models from Non-sequence Data via Tensor Decomposition. NIPS (2013)
Junier B. Oliva, Barnabás Póczos, Timothy D. Verstynen, Aarti Singh, Jeff G. Schneider, Fang-Cheng Yeh, Wen-Yih Isaac Tseng
FuSSO: Functional Shrinkage and Selection Operator. CoRR (2013)
Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing
Fast Distribution To Real Regression. CoRR (2013)
Xuezhi Wang, Roman Garnett, Jeff G. Schneider
Active search on graphs. KDD (2013)
Andrew W. Moore, Jeff G. Schneider
Real-valued All-Dimensions search: Low-overhead rapid searching over subsets of attributes CoRR (2013)
Tzu-Kuo Huang, Jeff G. Schneider
Spectral Learning of Hidden Markov Models from Dynamic and Static Data. ICML (3) (2013)
Yifei Ma, Roman Garnett, Jeff G. Schneider
Σ-Optimality for Active Learning on Gaussian Random Fields. NIPS (2013)
Liang Xiong, Barnabás Póczos, Jeff G. Schneider
Efficient Learning on Point Sets. ICDM (2013)
Matthew Tesch, Jeff G. Schneider, Howie Choset
Expensive multiobjective optimization for robotics. ICRA (2013)
Matthew Tesch, Jeff G. Schneider, Howie Choset
Expensive Function Optimization with Stochastic Binary Outcomes. ICML (3) (2013)
Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider
Distribution to Distribution Regression. ICML (3) (2013)
Danica J. Sutherland, Barnabás Póczos, Jeff G. Schneider
Active learning and search on low-rank matrices. KDD (2013)
Tzu-Kuo Huang, Jeff G. Schneider
Learning Bi-clustered Vector Autoregressive Models. ECML/PKDD (2) (2012)
Barnabás Póczos, Jeff G. Schneider
Nonparametric Estimation of Conditional Information and Divergences. AISTATS (2012)
Yi Zhang, Jeff G. Schneider
A Composite Likelihood View for Multi-Label Classification. AISTATS (2012)
Roman Garnett, Yamuna Krishnamurthy, Xuehan Xiong, Jeff G. Schneider, Richard P. Mann
Bayesian Optimal Active Search and Surveying. ICML (2012)
Yifei Ma, Roman Garnett, Jeff G. Schneider
Submodularity in Batch Active Learning and Survey Problems on Gaussian Random Fields CoRR (2012)
Barnabás Póczos, Zoubin Ghahramani, Jeff G. Schneider
Copula-based Kernel Dependency Measures. ICML (2012)
Yi Zhang, Jeff G. Schneider
Maximum Margin Output Coding. ICML (2012)
Barnabás Póczos, Liang Xiong, Jeff G. Schneider
Nonparametric Divergence Estimation with Applications to Machine Learning on Distributions CoRR (2012)
Barnabás Póczos, Liang Xiong, Danica J. Sutherland, Jeff G. Schneider
Support Distribution Machines CoRR (2012)
Barnabás Póczos, Liang Xiong, Danica J. Sutherland, Jeff G. Schneider
Nonparametric kernel estimators for image classification. CVPR (2012)
Barnabás Póczos, Zoubin Ghahramani, Jeff G. Schneider
Copula-based Kernel Dependency Measures CoRR (2012)
Jieyue Li, Liang Xiong, Jeff G. Schneider, Robert F. Murphy
Protein subcellular location pattern classification in cellular images using latent discriminative models. Bioinform. 28 (12) (2012)
Tzu-Kuo Huang, Jeff G. Schneider
Learning Auto-regressive Models from Sequence and Non-sequence Data. NIPS (2011)
Barnabás Póczos, Zoltán Szabó, Jeff G. Schneider
Nonparametric divergence estimators for independent subspace analysis. EUSIPCO (2011)
Barnabás Póczos, Liang Xiong, Jeff G. Schneider
Nonparametric Divergence Estimation with Applications to Machine Learning on Distributions. UAI (2011)
Liang Xiong, Xi Chen, Jeff G. Schneider
Direct Robust Matrix Factorizatoin for Anomaly Detection. ICDM (2011)
Yi Zhang, Jeff G. Schneider
Multi-Label Output Codes using Canonical Correlation Analysis. AISTATS (2011)
Barnabás Póczos, Jeff G. Schneider
On the Estimation of alpha-Divergences. AISTATS (2011)
Liang Xiong, Barnabás Póczos, Jeff G. Schneider
Group Anomaly Detection using Flexible Genre Models. NIPS (2011)
Liang Xiong, Barnabás Póczos, Jeff G. Schneider, Andrew J. Connolly, Jake VanderPlas
Hierarchical Probabilistic Models for Group Anomaly Detection. AISTATS (2011)
Matthew Tesch, Jeff G. Schneider, Howie Choset
Adapting control policies for expensive systems to changing environments. IROS (2011)
Matthew Tesch, Jeff G. Schneider, Howie Choset
Using response surfaces and expected improvement to optimize snake robot gait parameters. IROS (2011)
Tzu-Kuo Huang, Le Song, Jeff G. Schneider
Learning Nonlinear Dynamic Models from Non-sequenced Data. AISTATS (2010)
Yi Zhang, Jeff G. Schneider, Artur Dubrawski
Learning Compressible Models. SDM (2010)

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Publication Activity (10 Years)

Top Topics

Top Venues

Jeff G. Schneider