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2010 – today
- 2018
[j3]Mustafa Mukadam, Jing Dong, Xinyan Yan, Frank Dellaert, Byron Boots:
Continuous-time Gaussian process motion planning via probabilistic inference. I. J. Robotics Res. 37(11) (2018)- [c57]Jing Dong, Byron Boots, Frank Dellaert, Ranveer Chandra, Sudipta N. Sinha:
Learning to Align Images Using Weak Geometric Supervision. 3DV 2018: 700-709 - [c56]Ching-An Cheng, Byron Boots:
Convergence of Value Aggregation for Imitation Learning. AISTATS 2018: 1801-1809 - [c55]Siddarth Srinivasan, Geoffrey J. Gordon, Byron Boots:
Learning Hidden Quantum Markov Models. AISTATS 2018: 1979-1987 - [c54]Joris Guérin, Byron Boots:
Improving Image Clustering With Multiple Pretrained CNN Feature Extractors. BMVC 2018: 51 - [c53]Jennifer L. Molnar, Ching-An Cheng, Lucas O. Tiziani, Byron Boots, Frank L. Hammond:
Optical Sensing and Control Methods for Soft Pneumatically Actuated Robotic Manipulators. ICRA 2018: 1-8 - [c52]Alexander Lambert, Amirreza Shaban, Amit Raj, Zhen Liu, Byron Boots:
Deep Forward and Inverse Perceptual Models for Tracking and Prediction. ICRA 2018: 675-682 - [c51]Jing Dong, Mustafa Mukadam, Byron Boots, Frank Dellaert:
Sparse Gaussian Processes on Matrix Lie Groups: A Unified Framework for Optimizing Continuous-Time Trajectories. ICRA 2018: 6497-6504 - [c50]Joris Guérin, Olivier Gibaru, Eric Nyiri, Stéphane Thiery, Byron Boots:
Semantically Meaningful View Selection. IROS 2018: 1061-1066 - [c49]Muhammad Asif Rana, Mustafa Mukadam, Seyed Reza Ahmadzadeh, Sonia Chernova, Byron Boots:
Learning Generalizable Robot Skills from Demonstrations in Cluttered Environments. IROS 2018: 4655-4660 - [c48]Wen Sun, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell:
Dual Policy Iteration. NeurIPS 2018: 7059-7069 - [c47]Brandon Amos, Ivan Dario Jimenez Rodriguez, Jacob Sacks, Byron Boots, J. Zico Kolter:
Differentiable MPC for End-to-end Planning and Control. NeurIPS 2018: 8299-8310 - [c46]Hugh Salimbeni, Ching-An Cheng, Byron Boots, Marc Peter Deisenroth:
Orthogonally Decoupled Variational Gaussian Processes. NeurIPS 2018: 8725-8734 - [c45]Siddarth Srinivasan, Carlton Downey, Byron Boots:
Learning and Inference in Hilbert Space with Quantum Graphical Models. NeurIPS 2018: 10359-10368 - [c44]Yunpeng Pan, Ching-An Cheng, Kamil Saigol, Keuntaek Lee, Xinyan Yan, Evangelos Theodorou, Byron Boots:
Agile Autonomous Driving using End-to-End Deep Imitation Learning. Robotics: Science and Systems 2018 - [c43]Krzysztof Choromanski, Vikas Sindhwani, Brandon Jones, Damien Jourdan, Maciej Chociej, Byron Boots:
Learning-based Air Data System for Safe and Efficient Control of Fixed-wing Aerial Vehicles. SSRR 2018: 1-8 - [c42]Ching-An Cheng, Xinyan Yan, Nolan Wagener, Byron Boots:
Fast Policy Learning through Imitation and Reinforcement. UAI 2018: 845-855 - [i40]Ching-An Cheng, Byron Boots:
Convergence of Value Aggregation for Imitation Learning. CoRR abs/1801.07292 (2018) - [i39]Ching-An Cheng, Xinyan Yan, Nolan Wagener, Byron Boots:
Fast Policy Learning through Imitation and Reinforcement. CoRR abs/1805.10413 (2018) - [i38]Wen Sun, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell:
Dual Policy Iteration. CoRR abs/1805.10755 (2018) - [i37]Wen Sun, J. Andrew Bagnell, Byron Boots:
Truncated Horizon Policy Search: Combining Reinforcement Learning & Imitation Learning. CoRR abs/1805.11240 (2018) - [i36]Ching-An Cheng, Xinyan Yan, Evangelos Theodorou, Byron Boots:
Model-Based Imitation Learning with Accelerated Convergence. CoRR abs/1806.04642 (2018) - [i35]Joris Guérin, Byron Boots:
Improving Image Clustering With Multiple Pretrained CNN Feature Extractors. CoRR abs/1807.07760 (2018) - [i34]Joris Guérin, Olivier Gibaru, Eric Nyiri, Stéphane Thiery, Byron Boots:
Semantically Meaningful View Selection. CoRR abs/1807.10303 (2018) - [i33]Mustafa Mukadam, Jing Dong, Frank Dellaert, Byron Boots:
STEAP: simultaneous trajectory estimation and planning. CoRR abs/1807.10425 (2018) - [i32]Muhammad Asif Rana, Mustafa Mukadam, Seyed Reza Ahmadzadeh, Sonia Chernova, Byron Boots:
Learning Generalizable Robot Skills from Demonstrations in Cluttered Environments. CoRR abs/1808.00349 (2018) - [i31]Jing Dong, Byron Boots, Frank Dellaert, Ranveer Chandra, Sudipta N. Sinha:
Learning to Align Images using Weak Geometric Supervision. CoRR abs/1808.01424 (2018) - [i30]Hugh Salimbeni, Ching-An Cheng, Byron Boots, Marc Peter Deisenroth:
Orthogonally Decoupled Variational Gaussian Processes. CoRR abs/1809.08820 (2018) - [i29]Balakumar Sundaralingam, Alexander Sasha Lambert, Ankur Handa, Byron Boots, Tucker Hermans, Stan Birchfield, Nathan D. Ratliff, Dieter Fox:
Robust Learning of Tactile Force Estimation through Robot Interaction. CoRR abs/1810.06187 (2018) - [i28]Ching-An Cheng, Xinyan Yan, Nathan D. Ratliff, Byron Boots:
Predictor-Corrector Policy Optimization. CoRR abs/1810.06509 (2018) - [i27]Amirreza Shaban, Ching-An Cheng, Nathan Hatch, Byron Boots:
Truncated Back-propagation for Bilevel Optimization. CoRR abs/1810.10667 (2018) - [i26]Siddarth Srinivasan, Carlton Downey, Byron Boots:
Learning and Inference in Hilbert Space with Quantum Graphical Models. CoRR abs/1810.12369 (2018) - [i25]Brandon Amos, Ivan Dario Jimenez Rodriguez, Jacob Sacks, Byron Boots, J. Zico Kolter:
Differentiable MPC for End-to-end Planning and Control. CoRR abs/1810.13400 (2018) - [i24]Ching-An Cheng, Mustafa Mukadam, Jan Issac, Stan Birchfield, Dieter Fox, Byron Boots, Nathan D. Ratliff:
RMPflow: A Computational Graph for Automatic Motion Policy Generation. CoRR abs/1811.07049 (2018) - 2017
- [j2]Xinyan Yan, Vadim Indelman, Byron Boots:
Incremental sparse GP regression for continuous-time trajectory estimation and mapping. Robotics and Autonomous Systems 87: 120-132 (2017) - [c41]Brian Hrolenok, Byron Boots, Tucker Hybinette Balch:
Sampling Beats Fixed Estimate Predictors for Cloning Stochastic Behavior in Multiagent Systems. AAAI 2017: 2022-2028 - [c40]Bo Dai, Niao He, Yunpeng Pan, Byron Boots, Le Song:
Learning from Conditional Distributions via Dual Embeddings. AISTATS 2017: 1458-1467 - [c39]Amirreza Shaban, Shray Bansal, Zhen Liu, Irfan Essa, Byron Boots:
One-Shot Learning for Semantic Segmentation. BMVC 2017 - [c38]Muhammad Asif Rana, Mustafa Mukadam, Seyed Reza Ahmadzadeh, Sonia Chernova, Byron Boots:
Towards Robust Skill Generalization: Unifying Learning from Demonstration and Motion Planning. CoRL 2017: 109-118 - [c37]Yunpeng Pan, Xinyan Yan, Evangelos A. Theodorou, Byron Boots:
Prediction under Uncertainty in Sparse Spectrum Gaussian Processes with Applications to Filtering and Control. ICML 2017: 2760-2768 - [c36]Wen Sun, Arun Venkatraman, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell:
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction. ICML 2017: 3309-3318 - [c35]Mustafa Mukadam, Ching-An Cheng, Xinyan Yan, Byron Boots:
Approximately optimal continuous-time motion planning and control via Probabilistic Inference. ICRA 2017: 664-671 - [c34]Grady Williams, Nolan Wagener, Brian Goldfain, Paul Drews, James M. Rehg, Byron Boots, Evangelos A. Theodorou:
Information theoretic MPC for model-based reinforcement learning. ICRA 2017: 1714-1721 - [c33]Jing Dong, John Gary Burnham, Byron Boots, Glen C. Rains, Frank Dellaert:
4D crop monitoring: Spatio-temporal reconstruction for agriculture. ICRA 2017: 3878-3885 - [c32]Eric Huang, Mustafa Mukadam, Zhen Liu, Byron Boots:
Motion planning with graph-based trajectories and Gaussian process inference. ICRA 2017: 5591-5598 - [c31]Arun Venkatraman, Nicholas Rhinehart, Wen Sun, Lerrel Pinto, Martial Hebert, Byron Boots, Kris M. Kitani, James Andrew Bagnell:
Predictive-State Decoders: Encoding the Future into Recurrent Networks. NIPS 2017: 1172-1183 - [c30]Ching-An Cheng, Byron Boots:
Variational Inference for Gaussian Process Models with Linear Complexity. NIPS 2017: 5190-5200 - [c29]Carlton Downey, Ahmed Hefny, Byron Boots, Geoffrey J. Gordon, Boyue Li:
Predictive State Recurrent Neural Networks. NIPS 2017: 6055-6066 - [c28]Eric Huang, Ankit Bhatia, Byron Boots, Matthew T. Mason:
Exact Bounds on the Contact Driven Motion of a Sliding Object, With Applications to Robotic Pulling. Robotics: Science and Systems 2017 - [c27]Mustafa Mukadam, Jing Dong, Frank Dellaert, Byron Boots:
Simultaneous Trajectory Estimation and Planning via Probabilistic Inference. Robotics: Science and Systems 2017 - [i23]Mustafa Mukadam, Ching-An Cheng, Xinyan Yan, Byron Boots:
Approximately Optimal Continuous-Time Motion Planning and Control via Probabilistic Inference. CoRR abs/1702.07335 (2017) - [i22]Wen Sun, Arun Venkatraman, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell:
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction. CoRR abs/1703.01030 (2017) - [i21]Jing Dong, Byron Boots, Frank Dellaert:
Sparse Gaussian Processes for Continuous-Time Trajectory Estimation on Matrix Lie Groups. CoRR abs/1705.06020 (2017) - [i20]Mustafa Mukadam, Jing Dong, Xinyan Yan, Frank Dellaert, Byron Boots:
Continuous-Time Gaussian Process Motion Planning via Probabilistic Inference. CoRR abs/1707.07383 (2017) - [i19]Amirreza Shaban, Shray Bansal, Zhen Liu, Irfan Essa, Byron Boots:
One-Shot Learning for Semantic Segmentation. CoRR abs/1709.03410 (2017) - [i18]Yunpeng Pan, Ching-An Cheng, Kamil Saigol, Keuntaek Lee, Xinyan Yan, Evangelos Theodorou, Byron Boots:
Agile Off-Road Autonomous Driving Using End-to-End Deep Imitation Learning. CoRR abs/1709.07174 (2017) - [i17]Arun Venkatraman, Nicholas Rhinehart, Wen Sun, Lerrel Pinto, Martial Hebert, Byron Boots, Kris M. Kitani, J. Andrew Bagnell:
Predictive-State Decoders: Encoding the Future into Recurrent Networks. CoRR abs/1709.08520 (2017) - [i16]Xinyan Yan, Krzysztof Choromanski, Byron Boots, Vikas Sindhwani:
Manifold Regularization for Kernelized LSTD. CoRR abs/1710.05387 (2017) - [i15]Alexander Lambert, Amirreza Shaban, Amit Raj, Zhen Liu, Byron Boots:
Deep Forward and Inverse Perceptual Models for Tracking and Prediction. CoRR abs/1710.11311 (2017) - [i14]Ching-An Cheng, Byron Boots:
Variational Inference for Gaussian Process Models with Linear Complexity. CoRR abs/1711.10127 (2017) - 2016
- [c26]Arun Venkatraman, Wen Sun, Martial Hebert, J. Andrew Bagnell, Byron Boots:
Online Instrumental Variable Regression with Applications to Online Linear System Identification. AAAI 2016: 2101-2107 - [c25]Yu Nishiyama, Amir Afsharinejad, Shunsuke Naruse, Byron Boots, Le Song:
The Nonparametric Kernel Bayes Smoother. AISTATS 2016: 547-555 - [c24]Wen Sun, Arun Venkatraman, Byron Boots, J. Andrew Bagnell:
Learning to Filter with Predictive State Inference Machines. ICML 2016: 1197-1205 - [c23]
- [c22]Arun Venkatraman, Wen Sun, Martial Hebert, Byron Boots, J. Andrew Bagnell:
Inference Machines for Nonparametric Filter Learning. IJCAI 2016: 2074-2081 - [c21]Jie Tan, Zhaoming Xie, Byron Boots, C. Karen Liu:
Simulation-based design of dynamic controllers for humanoid balancing. IROS 2016: 2729-2736 - [c20]Ching-An Cheng, Byron Boots:
Incremental Variational Sparse Gaussian Process Regression. NIPS 2016: 4403-4411 - [c19]Jing Dong, Mustafa Mukadam, Frank Dellaert, Byron Boots:
Motion Planning as Probabilistic Inference using Gaussian Processes and Factor Graphs. Robotics: Science and Systems 2016 - [c18]Zita Marinho, Byron Boots, Anca D. Dragan, Arunkumar Byravan, Geoffrey J. Gordon, Siddhartha Srinivasa:
Functional Gradient Motion Planning in Reproducing Kernel Hilbert Spaces. Robotics: Science and Systems 2016 - [c17]Wen Sun, Roberto Capobianco, Geoffrey J. Gordon, J. Andrew Bagnell, Byron Boots:
Learning to Smooth with Bidirectional Predictive State Inference Machines. UAI 2016 - [i13]Zita Marinho, Anca D. Dragan, Arunkumar Byravan, Byron Boots, Siddhartha S. Srinivasa, Geoffrey J. Gordon:
Functional Gradient Motion Planning in Reproducing Kernel Hilbert Spaces. CoRR abs/1601.03648 (2016) - [i12]Bo Dai, Niao He, Yunpeng Pan, Byron Boots, Le Song:
Learning from Conditional Distributions via Dual Kernel Embeddings. CoRR abs/1607.04579 (2016) - [i11]Yunpeng Pan, Xinyan Yan, Evangelos Theodorou, Byron Boots:
Adaptive Probabilistic Trajectory Optimization via Efficient Approximate Inference. CoRR abs/1608.06235 (2016) - [i10]Jing Dong, John Gary Burnham, Byron Boots, Glen C. Rains, Frank Dellaert:
4D Crop Monitoring: Spatio-Temporal Reconstruction for Agriculture. CoRR abs/1610.02482 (2016) - 2015
- [c16]Arunkumar Byravan, Mathew Monfort, Brian D. Ziebart, Byron Boots, Dieter Fox:
Graph-Based Inverse Optimal Control for Robot Manipulation. IJCAI 2015: 1874-1880 - [c15]Xinyan Yan, Vadim Indelman, Byron Boots:
Incremental Sparse GP Regression for Continuous-Time Trajectory Estimation and Mapping. ISRR (2) 2015: 545-561 - [c14]Amirreza Shaban, Mehrdad Farajtabar, Bo Xie, Le Song, Byron Boots:
Learning Latent Variable Models by Improving Spectral Solutions with Exterior Point Method. UAI 2015: 792-801 - [i9]Xinyan Yan, Vadim Indelman, Byron Boots:
Incremental Sparse GP Regression for Continuous-time Trajectory Estimation & Mapping. CoRR abs/1504.02696 (2015) - [i8]Wen Sun, Arun Venkatraman, Byron Boots, J. Andrew Bagnell:
Learning to Filter with Predictive State Inference Machines. CoRR abs/1512.08836 (2015) - 2014
- [c13]Byron Boots, Arunkumar Byravan, Dieter Fox:
Learning predictive models of a depth camera & manipulator from raw execution traces. ICRA 2014: 4021-4028 - [c12]Arunkumar Byravan, Byron Boots, Siddhartha S. Srinivasa, Dieter Fox:
Space-time functional gradient optimization for motion planning. ICRA 2014: 6499-6506 - 2013
- [c11]Byron Boots, Geoffrey J. Gordon:
A Spectral Learning Approach to Range-Only SLAM. ICML (1) 2013: 19-26 - [c10]Byron Boots, Geoffrey J. Gordon, Arthur Gretton:
Hilbert Space Embeddings of Predictive State Representations. UAI 2013 - [i7]Byron Boots, Geoffrey J. Gordon, Arthur Gretton:
Hilbert Space Embeddings of Predictive State Representations. CoRR abs/1309.6819 (2013) - 2012
- [c9]Byron Boots, Geoffrey J. Gordon:
Two Manifold Problems with Applications to Nonlinear System Identification. ICML 2012 - [i6]Byron Boots, Geoffrey J. Gordon:
Two-Manifold Problems with Applications to Nonlinear System Identification. CoRR abs/1206.4648 (2012) - [i5]Byron Boots, Geoffrey J. Gordon:
A Spectral Learning Approach to Range-Only SLAM. CoRR abs/1207.2491 (2012) - 2011
- [j1]Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon:
Closing the learning-planning loop with predictive state representations. I. J. Robotics Res. 30(7): 954-966 (2011) - [c8]Byron Boots, Geoffrey J. Gordon:
An Online Spectral Learning Algorithm for Partially Observable Nonlinear Dynamical Systems. AAAI 2011 - [i4]
- 2010
- [c7]Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon:
Closing the learning-planning loop with predictive state representations. AAMAS 2010: 1369-1370 - [c6]Le Song, Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon, Alexander J. Smola:
Hilbert Space Embeddings of Hidden Markov Models. ICML 2010: 991-998 - [c5]
- [c4]Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon:
Closing the Learning-Planning Loop with Predictive State Representations. Robotics: Science and Systems 2010 - [c3]Sajid M. Siddiqi, Byron Boots, Geoffrey J. Gordon:
Reduced-Rank Hidden Markov Models. AISTATS 2010: 741-748 - [i3]Byron Boots, Geoffrey J. Gordon:
Predictive State Temporal Difference Learning. CoRR abs/1011.0041 (2010)
2000 – 2009
- 2009
- [i2]Sajid M. Siddiqi, Byron Boots, Geoffrey J. Gordon:
Reduced-Rank Hidden Markov Models. CoRR abs/0910.0902 (2009) - [i1]Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon:
Closing the Learning-Planning Loop with Predictive State Representations. CoRR abs/0912.2385 (2009) - 2008
- [p1]Eric Chown, Byron Boots:
Learning Cognitive Maps: Finding Useful Structure in an Uncertain World. Robotics and Cognitive Approaches to Spatial Mapping 2008: 215-236 - 2007
- [c2]Sajid M. Siddiqi, Byron Boots, Geoffrey J. Gordon:
A Constraint Generation Approach to Learning Stable Linear Dynamical Systems. NIPS 2007: 1329-1336 - 2005
- [c1]Stephen M. Majercik, Byron Boots:
DC-SSAT: A Divide-and-Conquer Approach to Solving Stochastic Satisfiability Problems Efficiently. AAAI 2005: 416-422
Coauthor Index
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