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ORCIDJeff G. Schneider
Jeff Schneider 0001
Person information
- affiliation: Carnegie Mellon University, The Robotics Institute
Other persons with the same name
- Jeff Schneider — disambiguation page
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2020 – today
- 2022
[j7]Conor Igoe
, Ramina Ghods, Jeff Schneider:
Multi-Agent Active Search: A Reinforcement Learning Approach. IEEE Robotics Autom. Lett. 7(2): 754-761 (2022)- [j6]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): 890-897 (2022) - [c117]Viraj Mehta, Biswajit Paria, Jeff Schneider, Stefano Ermon, Willie Neiswanger:
An Experimental Design Perspective on Model-Based Reinforcement Learning. ICLR 2022 - [c116]Adam R. Villaflor, Zhe Huang, Swapnil Pande, John M. Dolan, Jeff Schneider:
Addressing Optimism Bias in Sequence Modeling for Reinforcement Learning. ICML 2022: 22270-22283 - [c115]Yeeho Song, Jeff Schneider:
Robust Reinforcement Learning via Genetic Curriculum. ICRA 2022: 5560-5566 - [c114]Divam Gupta, Wei Pu, Trenton Tabor, Jeff Schneider:
SBEVNet: End-to-End Deep Stereo Layout Estimation. WACV 2022: 667-676 - [i51]David Guttendorf, D. W. Wilson Hamilton, Anne Harris Heckman, Herman Herman, Felix Jonathan, Prasanna Kannappan, Nicholas Mireles, Luis E. Navarro-Serment, Jean Oh, Wei Pu, Rohan Saxena, Jeff Schneider, Matt Schnur, Carter Tiernan, Trenton Tabor:
UGV-UAV Object Geolocation in Unstructured Environments. CoRR abs/2201.05518 (2022) - [i50]Yeeho Song, Jeff Schneider:
Robust Reinforcement Learning via Genetic Curriculum. CoRR abs/2202.08393 (2022) - [i49]Arundhati Banerjee, Ramina Ghods, Jeff Schneider:
Multi-Agent Active Search using Detection and Location Uncertainty. CoRR abs/2203.04524 (2022) - [i48]Ian Char, Viraj Mehta, Adam Villaflor, John M. Dolan, Jeff Schneider:
BATS: Best Action Trajectory Stitching. CoRR abs/2204.12026 (2022) - [i47]Conor Igoe, Youngseog Chung, Ian Char, Jeff Schneider:
How Useful are Gradients for OOD Detection Really? CoRR abs/2205.10439 (2022) - [i46]Adam Villaflor, Zhe Huang, Swapnil Pande, John M. Dolan, Jeff Schneider:
Addressing Optimism Bias in Sequence Modeling for Reinforcement Learning. CoRR abs/2207.10295 (2022) - [i45]Arundhati Banerjee, Ramina Ghods, Jeff Schneider:
Cost Aware Asynchronous Multi-Agent Active Search. CoRR abs/2210.02259 (2022) - [i44]Viraj Mehta, Ian Char, Joseph Abbate, Rory Conlin, Mark D. Boyer, Stefano Ermon, Jeff Schneider, Willie Neiswanger:
Exploration via Planning for Information about the Optimal Trajectory. CoRR abs/2210.04642 (2022) - [i43]Xiang Li, Viraj Mehta, Johannes Kirschner, Ian Char, Willie Neiswanger, Jeff Schneider, Andreas Krause, Ilija Bogunovic:
Near-optimal Policy Identification in Active Reinforcement Learning. CoRR abs/2212.09510 (2022) - 2021
- [c113]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: 3735-3742 - [c112]Zhiqian Qiao, Jeff Schneider, John M. Dolan:
Behavior Planning at Urban Intersections through Hierarchical Reinforcement Learning*. ICRA 2021: 2667-2673 - [c111]Ramina Ghods, William J. Durkin, Jeff Schneider:
Multi-Agent Active Search using Realistic Depth-Aware Noise Model. ICRA 2021: 9101-9108 - [c110]Tanmay Agarwal, Hitesh Arora, Jeff Schneider:
Learning Urban Driving Policies using Deep Reinforcement Learning. ITSC 2021: 607-614 - [c109]Youngseog Chung, Willie Neiswanger, Ian Char, Jeff Schneider:
Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification. NeurIPS 2021: 10971-10984 - [c108]Ramina Ghods, Arundhati Banerjee, Jeff Schneider:
Decentralized multi-agent active search for sparse signals. UAI 2021: 696-706 - [i42]Tanmay Agarwal, Hitesh Arora, Jeff Schneider:
Affordance-based Reinforcement Learning for Urban Driving. CoRR abs/2101.05970 (2021) - [i41]Divam Gupta, Wei Pu, Trenton Tabor, Jeff Schneider:
SBEVNet: End-to-End Deep Stereo Layout Estimation. CoRR abs/2105.11705 (2021) - [i40]Youngseog Chung, Ian Char, Han Guo, Jeff Schneider, Willie Neiswanger:
Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing, and Improving Uncertainty Quantification. CoRR abs/2109.10254 (2021) - [i39]Viraj Mehta, Biswajit Paria, Jeff Schneider, Stefano Ermon, Willie Neiswanger:
An Experimental Design Perspective on Model-Based Reinforcement Learning. CoRR abs/2112.05244 (2021) - [i38]Benjamin Freed, Aditya Kapoor, Ian Abraham, Jeff G. Schneider, Howie Choset:
Learning Cooperative Multi-Agent Policies with Partial Reward Decoupling. CoRR abs/2112.12740 (2021) - 2020
- [j5]Kirthevasan Kandasamy, Karun Raju Vysyaraju, Willie Neiswanger, Biswajit Paria, Christopher R. Collins, Jeff Schneider, Barnabás Póczos, Eric P. Xing:
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly. J. Mach. Learn. Res. 21: 81:1-81:27 (2020) - [c107]Ksenia Korovina, Sailun Xu, Kirthevasan Kandasamy, Willie Neiswanger, Barnabás Póczos, Jeff Schneider, Eric P. Xing:
ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations. AISTATS 2020: 3393-3403 - [c106]Zhiqian Qiao, Jing Zhao, Jin Zhu, Zachariah Tyree, Priyantha Mudalige, Jeff Schneider, John M. Dolan:
Human Driver Behavior Prediction based on UrbanFlow*. ICRA 2020: 10570-10576 - [c105]Zhiqian Qiao, Zachariah Tyree, Priyantha Mudalige, Jeff Schneider, John M. Dolan:
Hierarchical Reinforcement Learning Method for Autonomous Vehicle Behavior Planning. IROS 2020: 6084-6089 - [i37]Youngseog Chung, Ian Char, Willie Neiswanger, Kirthevasan Kandasamy, Andrew Oakleigh Nelson, Mark D. Boyer, Egemen Kolemen, Jeff Schneider:
Offline Contextual Bayesian Optimization for Nuclear Fusion. CoRR abs/2001.01793 (2020) - [i36]Viraj Mehta, Ian Char, Willie Neiswanger, Youngseog Chung, Andrew Oakleigh Nelson, Mark D. Boyer, Egemen Kolemen, Jeff Schneider:
Neural Dynamical Systems: Balancing Structure and Flexibility in Physical Prediction. CoRR abs/2006.12682 (2020) - [i35]Ramina Ghods, Arundhati Banerjee, Jeff Schneider:
Asynchronous Multi Agent Active Search. CoRR abs/2006.14718 (2020) - [i34]Zhiqian Qiao, Jeff Schneider, John M. Dolan:
Behavior Planning at Urban Intersections through Hierarchical Reinforcement Learning. CoRR abs/2011.04697 (2020) - [i33]Ramina Ghods, William J. Durkin, Jeff Schneider:
Multi-Agent Active Search using Realistic Depth-Aware Noise Model. CoRR abs/2011.04825 (2020) - [i32]Youngseog Chung, Willie Neiswanger, Ian Char, Jeff Schneider:
Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification. CoRR abs/2011.09588 (2020)
2010 – 2019
- 2019
- [j4]Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos:
Multi-fidelity Gaussian Process Bandit Optimisation. J. Artif. Intell. Res. 66: 151-196 (2019) - [c104]Kirthevasan Kandasamy, Willie Neiswanger, Reed Zhang, Akshay Krishnamurthy, Jeff Schneider, Barnabás Póczos:
Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments. ICML 2019: 3222-3232 - [i31]Willie Neiswanger, Kirthevasan Kandasamy, Barnabás Póczos, Jeff Schneider, Eric P. Xing:
ProBO: a Framework for Using Probabilistic Programming in Bayesian Optimization. CoRR abs/1901.11515 (2019) - [i30]Kirthevasan Kandasamy, Karun Raju Vysyaraju, Willie Neiswanger, Biswajit Paria, Christopher R. Collins, Jeff Schneider, Barnabás Póczos, Eric P. Xing:
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly. CoRR abs/1903.06694 (2019) - [i29]Ksenia Korovina, Sailun Xu, Kirthevasan Kandasamy, Willie Neiswanger, Barnabás Póczos, Jeff Schneider, Eric P. Xing:
ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations. CoRR abs/1908.01425 (2019) - [i28]Zhiqian Qiao, Zachariah Tyree, Priyantha Mudalige, Jeff Schneider, John M. Dolan:
Hierarchical Reinforcement Learning Method for Autonomous Vehicle Behavior Planning. CoRR abs/1911.03799 (2019) - [i27]Zhiqian Qiao, Jing Zhao, Zachariah Tyree, Priyantha Mudalige, Jeff Schneider, John M. Dolan:
Human Driver Behavior Prediction based on UrbanFlow. CoRR abs/1911.03801 (2019) - 2018
- [c103]Kirthevasan Kandasamy, Akshay Krishnamurthy, Jeff Schneider, Barnabás Póczos:
Parallelised Bayesian Optimisation via Thompson Sampling. AISTATS 2018: 133-142 - [c102]Junier B. Oliva, Avinava Dubey, Manzil Zaheer, Barnabás Póczos, Ruslan Salakhutdinov, Eric P. Xing, Jeff Schneider:
Transformation Autoregressive Networks. ICML 2018: 3895-3904 - [c101]Kirthevasan Kandasamy, Willie Neiswanger, Jeff Schneider, Barnabás Póczos, Eric P. Xing:
Neural Architecture Search with Bayesian Optimisation and Optimal Transport. NeurIPS 2018: 2020-2029 - [i26]Kirthevasan Kandasamy, Willie Neiswanger, Jeff Schneider, Barnabás Póczos, Eric P. Xing:
Neural Architecture Search with Bayesian Optimisation and Optimal Transport. CoRR abs/1802.07191 (2018) - [i25]Kirthevasan Kandasamy, Willie Neiswanger, Reed Zhang, Akshay Krishnamurthy, Jeff Schneider, Barnabás Póczos:
Myopic Bayesian Design of Experiments via Posterior Sampling and Probabilistic Programming. CoRR abs/1805.09964 (2018) - 2017
- [j3]Kirthevasan Kandasamy, Jeff G. Schneider, Barnabás Póczos:
Query efficient posterior estimation in scientific experiments via Bayesian active learning. Artif. Intell. 243: 45-56 (2017) - [c100]Siamak Ravanbakhsh, François Lanusse, Rachel Mandelbaum, Jeff G. Schneider, Barnabás Póczos:
Enabling Dark Energy Science with Deep Generative Models of Galaxy Images. AAAI 2017: 1488-1494 - [c99]Yifei Ma, Roman Garnett, Jeff G. Schneider:
Active Search for Sparse Signals with Region Sensing. AAAI 2017: 2315-2321 - [c98]Jeff G. Schneider:
Active Optimization and Self Driving Cars. AAMAS 2017: 3 - [c97]Siamak Ravanbakhsh, Jeff G. Schneider, Barnabás Póczos:
Deep Learning with Sets and Point Clouds. ICLR (Workshop) 2017 - [c96]Kirthevasan Kandasamy, Gautam Dasarathy, Jeff G. Schneider, Barnabás Póczos:
Multi-fidelity Bayesian Optimisation with Continuous Approximations. ICML 2017: 1799-1808 - [c95]Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider:
The Statistical Recurrent Unit. ICML 2017: 2671-2680 - [c94]Siamak Ravanbakhsh, Jeff G. Schneider, Barnabás Póczos:
Equivariance Through Parameter-Sharing. ICML 2017: 2892-2901 - [c93]Sibi Venkatesan, James K. Miller, Jeff Schneider, Artur Dubrawski:
Scaling Active Search using Linear Similarity Functions. IJCAI 2017: 2878-2884 - [i24]Siamak Ravanbakhsh, Jeff G. Schneider, Barnabás Póczos:
Equivariance Through Parameter-Sharing. CoRR abs/1702.08389 (2017) - [i23]Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider:
The Statistical Recurrent Unit. CoRR abs/1703.00381 (2017) - [i22]Sibi Venkatesan, James K. Miller, Jeff Schneider, Artur Dubrawski:
Scaling Active Search using Linear Similarity Functions. CoRR abs/1705.00334 (2017) - [i21]Kirthevasan Kandasamy, Akshay Krishnamurthy, Jeff G. Schneider, Barnabás Póczos:
Asynchronous Parallel Bayesian Optimisation via Thompson Sampling. CoRR abs/1705.09236 (2017) - [i20]Junier B. Oliva, Kumar Avinava Dubey, Barnabás Póczos, Eric P. Xing, Jeff G. Schneider:
Recurrent Estimation of Distributions. CoRR abs/1705.10750 (2017) - [i19]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 abs/1711.02033 (2017) - 2016
- [c92]Danica J. Sutherland, Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider:
Linear-Time Learning on Distributions with Approximate Kernel Embeddings. AAAI 2016: 2073-2079 - [c91]Siamak Ravanbakhsh, Barnabás Póczos, Jeff G. Schneider, Dale Schuurmans, Russell Greiner:
Stochastic Neural Networks with Monotonic Activation Functions. AISTATS 2016: 809-818 - [c90]Chun-Liang Li, Kirthevasan Kandasamy, Barnabás Póczos, Jeff G. Schneider:
High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models. AISTATS 2016: 884-892 - [c89]Junier B. Oliva, Avinava Dubey, Andrew Gordon Wilson, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing:
Bayesian Nonparametric Kernel-Learning. AISTATS 2016: 1078-1086 - [c88]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: 2407-2416 - [c87]Xuezhi Wang, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos:
Nonparametric Risk and Stability Analysis for Multi-Task Learning Problems. IJCAI 2016: 2146-2152 - [c86]Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos:
Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations. NIPS 2016: 992-1000 - [c85]Kirthevasan Kandasamy, Gautam Dasarathy, Barnabás Póczos, Jeff G. Schneider:
The Multi-fidelity Multi-armed Bandit. NIPS 2016: 1777-1785 - [i18]Siamak Ravanbakhsh, Barnabás Póczos, Jeff G. Schneider, Dale Schuurmans, Russell Greiner:
Stochastic Neural Networks with Monotonic Activation Functions. CoRR abs/1601.00034 (2016) - [i17]Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos:
Multi-fidelity Gaussian Process Bandit Optimisation. CoRR abs/1603.06288 (2016) - [i16]Siamak Ravanbakhsh, François Lanusse, Rachel Mandelbaum, Jeff G. Schneider, Barnabás Póczos:
Enabling Dark Energy Science with Deep Generative Models of Galaxy Images. CoRR abs/1609.05796 (2016) - [i15]Kirthevasan Kandasamy, Gautam Dasarathy, Jeff G. Schneider, Barnabás Póczos:
The Multi-fidelity Multi-armed Bandit. CoRR abs/1610.09726 (2016) - [i14]Siamak Ravanbakhsh, Jeff G. Schneider, Barnabás Póczos:
Deep Learning with Sets and Point Clouds. CoRR abs/1611.04500 (2016) - [i13]Yifei Ma, Roman Garnett, Jeff G. Schneider:
Active Search for Sparse Signals with Region Sensing. CoRR abs/1612.00583 (2016) - 2015
- [c84]Yifei Ma, Danica J. Sutherland, Roman Garnett, Jeff G. Schneider:
Active Pointillistic Pattern Search. AISTATS 2015 - [c83]Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Eric P. Xing, Hy Trac, Shirley Ho, Jeff G. Schneider:
Fast Function to Function Regression. AISTATS 2015 - [c82]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: 664-669 - [c81]Kirthevasan Kandasamy, Jeff G. Schneider, Barnabás Póczos:
High Dimensional Bayesian Optimisation and Bandits via Additive Models. ICML 2015: 295-304 - [c80]Roman Garnett, Shirley Ho, Jeff G. Schneider:
Finding Galaxies in the Shadows of Quasars with Gaussian Processes. ICML 2015: 1025-1033 - [c79]Kirthevasan Kandasamy, Jeff G. Schneider, Barnabás Póczos:
Bayesian Active Learning for Posterior Estimation - IJCAI-15 Distinguished Paper. IJCAI 2015: 3605-3611 - [c78]Yifei Ma, Tzu-Kuo Huang, Jeff G. Schneider:
Active Search and Bandits on Graphs using Sigma-Optimality. UAI 2015: 542-551 - [c77]Danica J. Sutherland, Jeff G. Schneider:
On the Error of Random Fourier Features. UAI 2015: 862-871 - [c76]Xuezhi Wang, Jeff G. Schneider:
Generalization Bounds for Transfer Learning under Model Shift. UAI 2015: 922-931 - [i12]Kirthevasan Kandasamy, Jeff G. Schneider, Barnabás Póczos:
High Dimensional Bayesian Optimisation and Bandits via Additive Models. CoRR abs/1503.01673 (2015) - [i11]Danica J. Sutherland, Jeff G. Schneider:
On the Error of Random Fourier Features. CoRR abs/1506.02785 (2015) - [i10]Danica J. Sutherland, Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider:
Linear-time Learning on Distributions with Approximate Kernel Embeddings. CoRR abs/1509.07553 (2015) - [i9]Junier B. Oliva, Danica J. Sutherland, Barnabás Póczos, Jeff G. Schneider:
Deep Mean Maps. CoRR abs/1511.04150 (2015) - 2014
- [c75]Yifei Ma, Roman Garnett, Jeff G. Schneider:
Active Area Search via Bayesian Quadrature. AISTATS 2014: 595-603 - [c74]Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing:
Fast Distribution To Real Regression. AISTATS 2014: 706-714 - [c73]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: 715-723 - [c72]Xuezhi Wang, Tzu-Kuo Huang, Jeff G. Schneider:
Active Transfer Learning under Model Shift. ICML 2014: 1305-1313 - [c71]Guillermo F. Cabrera, Christopher J. Miller, Jeff G. Schneider:
Systematic Labeling Bias: De-biasing Where Everyone is Wrong. ICPR 2014: 4417-4422 - [c70]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: 119-123 - [c69]Xuezhi Wang, Jeff G. Schneider:
Flexible Transfer Learning under Support and Model Shift. NIPS 2014: 1898-1906 - [c68]Liang Xiong, Jeff G. Schneider:
Learning from Point Sets with Observational Bias. UAI 2014: 898-906 - [i8]Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Eric P. Xing, Jeff G. Schneider:
Fast Function to Function Regression. CoRR abs/1410.7414 (2014) - 2013
- [c67]Liang Xiong, Barnabás Póczos, Jeff G. Schneider:
Efficient Learning on Point Sets. ICDM 2013: 847-856 - [c66]Tzu-Kuo Huang, Jeff G. Schneider:
Spectral Learning of Hidden Markov Models from Dynamic and Static Data. ICML (3) 2013: 630-638 - [c65]Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider:
Distribution to Distribution Regression. ICML (3) 2013: 1049-1057 - [c64]Matthew Tesch, Jeff G. Schneider, Howie Choset:
Expensive Function Optimization with Stochastic Binary Outcomes. ICML (3) 2013: 1283-1291 - [c63]Matthew Tesch, Jeff G. Schneider, Howie Choset:
Expensive multiobjective optimization for robotics. ICRA 2013: 973-980 - [c62]Danica J. Sutherland, Barnabás Póczos, Jeff G. Schneider:
Active learning and search on low-rank matrices. KDD 2013: 212-220 - [c61]Xuezhi Wang, Roman Garnett, Jeff G. Schneider:
Active search on graphs. KDD 2013: 731-738 - [c60]Tzu-Kuo Huang, Jeff G. Schneider:
Learning Hidden Markov Models from Non-sequence Data via Tensor Decomposition. NIPS 2013: 333-341 - [c59]Yifei Ma, Roman Garnett, Jeff G. Schneider:
Σ-Optimality for Active Learning on Gaussian Random Fields. NIPS 2013: 2751-2759 - [i7]Andrew W. Moore, Jeff G. Schneider:
Real-valued All-Dimensions search: Low-overhead rapid searching over subsets of attributes. CoRR abs/1301.0589 (2013) - [i6]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 abs/1311.2234 (2013) - [i5]Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing:
Fast Distribution To Real Regression. CoRR abs/1311.2236 (2013) - 2012
- [j2]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): 32-39 (2012) - [c58]Barnabás Póczos, Liang Xiong, Danica J. Sutherland, Jeff G. Schneider:
Nonparametric kernel estimators for image classification. CVPR 2012: 2989-2996 - [c57]Roman Garnett, Yamuna Krishnamurthy, Xuehan Xiong, Jeff G. Schneider, Richard P. Mann:
Bayesian Optimal Active Search and Surveying. ICML 2012 - [c56]Barnabás Póczos, Zoubin Ghahramani, Jeff G. Schneider:
Copula-based Kernel Dependency Measures. ICML 2012 - [c55]Yi Zhang, Jeff G. Schneider:
Maximum Margin Output Coding. ICML 2012 - [c54]Tzu-Kuo Huang, Jeff G. Schneider:
Learning Bi-clustered Vector Autoregressive Models. ECML/PKDD (2) 2012: 741-756 - [c53]Barnabás Póczos, Jeff G. Schneider:
Nonparametric Estimation of Conditional Information and Divergences. AISTATS 2012: 914-923 - [c52]Yi Zhang, Jeff G. Schneider:
A Composite Likelihood View for Multi-Label Classification. AISTATS 2012: 1407-1415 - [i4]Barnabás Póczos, Liang Xiong, Danica J. Sutherland, Jeff G. Schneider:
Support Distribution Machines. CoRR abs/1202.0302 (2012) - [i3]Barnabás Póczos, Liang Xiong, Jeff G. Schneider:
Nonparametric Divergence Estimation with Applications to Machine Learning on Distributions. CoRR abs/1202.3758 (2012) - [i2]Barnabás Póczos, Zoubin Ghahramani, Jeff G. Schneider:
Copula-based Kernel Dependency Measures. CoRR abs/1206.4682 (2012) - [i1]Yifei Ma, Roman Garnett, Jeff G. Schneider:
Submodularity in Batch Active Learning and Survey Problems on Gaussian Random Fields. CoRR abs/1209.3694 (2012) - 2011
- [c51]Barnabás Póczos, Zoltán Szabó, Jeff G. Schneider:
Nonparametric divergence estimators for independent subspace analysis. EUSIPCO 2011: 1718-1722 - [c50]Liang Xiong, Xi Chen, Jeff G. Schneider:
Direct Robust Matrix Factorizatoin for Anomaly Detection. ICDM 2011: 844-853 - [c49]Matthew Tesch, Jeff G. Schneider, Howie Choset:
Adapting control policies for expensive systems to changing environments. IROS 2011: 357-364 - [c48]Matthew Tesch, Jeff G. Schneider, Howie Choset:
Using response surfaces and expected improvement to optimize snake robot gait parameters. IROS 2011: 1069-1074 - [c47]Liang Xiong, Barnabás Póczos, Jeff G. Schneider:
Group Anomaly Detection using Flexible Genre Models. NIPS 2011: 1071-1079 - [c46]