J. Andrew Bagnell

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 66

Top Venues

CoRR

AAAI

Robotics: Science and Systems

Auton. Robots

Publications

Yuda Song, J. Andrew Bagnell, Aarti Singh
Hybrid Reinforcement Learning from Offline Observation Alone. CoRR (2024)
Juntao Ren, Gokul Swamy, Zhiwei Steven Wu, J. Andrew Bagnell, Sanjiban Choudhury
Hybrid Inverse Reinforcement Learning. CoRR (2024)
David Wu, Gokul Swamy, J. Andrew Bagnell, Zhiwei Steven Wu, Sanjiban Choudhury
The Virtues of Pessimism in Inverse Reinforcement Learning. CoRR (2024)
Yuda Song, Gokul Swamy, Aarti Singh, J. Andrew Bagnell, Wen Sun
Understanding Preference Fine-Tuning Through the Lens of Coverage. CoRR (2024)
Zhaolin Gao, Jonathan D. Chang, Wenhao Zhan, Owen Oertell, Gokul Swamy, Kianté Brantley, Thorsten Joachims, J. Andrew Bagnell, Jason D. Lee, Wen Sun
REBEL: Reinforcement Learning via Regressing Relative Rewards. CoRR (2024)
Anirudh Vemula, Yuda Song, Aarti Singh, J. Andrew Bagnell, Sanjiban Choudhury
The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms. CoRR (2023)
Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu
Inverse Reinforcement Learning without Reinforcement Learning. CoRR (2023)
Anirudh Vemula, Wen Sun, Maxim Likhachev, J. Andrew Bagnell
On the Effectiveness of Iterative Learning Control. L4DC (2022)
Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu
Game-Theoretic Algorithms for Conditional Moment Matching. CoRR (2022)
Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu
Causal Imitation Learning under Temporally Correlated Noise. CoRR (2022)
Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu
Sequence Model Imitation Learning with Unobserved Contexts. NeurIPS (2022)
Yuda Song, Yifei Zhou, Ayush Sekhari, J. Andrew Bagnell, Akshay Krishnamurthy, Wen Sun
Hybrid RL: Using Both Offline and Online Data Can Make RL Efficient. CoRR (2022)
Gokul Swamy, Nived Rajaraman, Matthew Peng, Sanjiban Choudhury, J. Andrew Bagnell, Steven Wu, Jiantao Jiao, Kannan Ramchandran
Minimax Optimal Online Imitation Learning via Replay Estimation. NeurIPS (2022)
Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu
Sequence Model Imitation Learning with Unobserved Contexts. CoRR (2022)
Gokul Swamy, Nived Rajaraman, Matthew Peng, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu, Jiantao Jiao, Kannan Ramchandran
Minimax Optimal Online Imitation Learning via Replay Estimation. CoRR (2022)
Gokul Swamy, Sanjiban Choudhury, Zhiwei Steven Wu, J. Andrew Bagnell
Of Moments and Matching: Trade-offs and Treatments in Imitation Learning. CoRR (2021)
Anirudh Vemula, J. Andrew Bagnell, Maxim Likhachev
CMAX++ : Leveraging Experience in Planning and Execution using Inaccurate Models. AAAI (2021)
Jonathan C. Spencer, Sanjiban Choudhury, Arun Venkatraman, Brian D. Ziebart, J. Andrew Bagnell
Feedback in Imitation Learning: The Three Regimes of Covariate Shift. CoRR (2021)
Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Steven Wu
Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap. ICML (2021)
Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu
A Critique of Strictly Batch Imitation Learning. CoRR (2021)
Anirudh Vemula, Wen Sun, Maxim Likhachev, J. Andrew Bagnell
On the Effectiveness of Iterative Learning Control. CoRR (2021)
Anirudh Vemula, J. Andrew Bagnell
TRON: A Fast Solver for Trajectory Optimization with Non-Smooth Cost Functions. CoRR (2020)
Anirudh Vemula, Wen Sun, J. Andrew Bagnell
Exploration in Action Space. CoRR (2020)
Anirudh Vemula, Yash Oza, J. Andrew Bagnell, Maxim Likhachev
Planning and Execution using Inaccurate Models with Provable Guarantees. Robotics: Science and Systems (2020)
Anirudh Vemula, J. Andrew Bagnell, Maxim Likhachev
CMAX++ : Leveraging Experience in Planning and Execution using Inaccurate Models. CoRR (2020)
Anirudh Vemula, J. Andrew Bagnell
Tron: A Fast Solver for Trajectory Optimization with Non-Smooth Cost Functions. CDC (2020)
Anirudh Vemula, Yash Oza, J. Andrew Bagnell, Maxim Likhachev
Planning and Execution using Inaccurate Models with Provable Guarantees. CoRR (2020)
Anirudh Vemula, Wen Sun, J. Andrew Bagnell
Contrasting Exploration in Parameter and Action Space: A Zeroth-Order Optimization Perspective. CoRR (2019)
Wen Sun, Anirudh Vemula, Byron Boots, J. Andrew Bagnell
Provably Efficient Imitation Learning from Observation Alone. CoRR (2019)
Hanzhang Hu, Debadeepta Dey, Martial Hebert, J. Andrew Bagnell
Learning Anytime Predictions in Neural Networks via Adaptive Loss Balancing. AAAI (2019)
Anirudh Vemula, Wen Sun, J. Andrew Bagnell
Contrasting Exploration in Parameter and Action Space: A Zeroth-Order Optimization Perspective. AISTATS (2019)
Takayuki Osa, Joni Pajarinen, Gerhard Neumann, J. Andrew Bagnell, Pieter Abbeel, Jan Peters
An Algorithmic Perspective on Imitation Learning. CoRR (2018)
Takayuki Osa, Joni Pajarinen, Gerhard Neumann, J. Andrew Bagnell, Pieter Abbeel, Jan Peters
An Algorithmic Perspective on Imitation Learning. Found. Trends Robotics 7 (1-2) (2018)
Shervin Javdani, Henny Admoni, Stefania Pellegrinelli, Siddhartha S. Srinivasa, J. Andrew Bagnell
Shared autonomy via hindsight optimization for teleoperation and teaming. Int. J. Robotics Res. 37 (7) (2018)
Wen Sun, J. Andrew Bagnell, Byron Boots
Truncated Horizon Policy Search: Combining Reinforcement Learning & Imitation Learning. CoRR (2018)
Wen Sun, J. Andrew Bagnell, Byron Boots
Truncated horizon Policy Search: Combining Reinforcement Learning & Imitation Learning. ICLR (Poster) (2018)
Wen Sun, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell
Dual Policy Iteration. CoRR (2018)
Wen Sun, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell
Dual Policy Iteration. NeurIPS (2018)
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 (2017)
Hanzhang Hu, Wen Sun, Arun Venkatraman, Martial Hebert, J. Andrew Bagnell
Gradient Boosting on Stochastic Data Streams. CoRR (2017)
Shervin Javdani, Henny Admoni, Stefania Pellegrinelli, Siddhartha S. Srinivasa, J. Andrew Bagnell
Shared Autonomy via Hindsight Optimization for Teleoperation and Teaming. CoRR (2017)
Wen Sun, Arun Venkatraman, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction. ICML (2017)
Jiaji Zhou, J. Andrew Bagnell, Matthew T. Mason
A Fast Stochastic Contact Model for Planar Pushing and Grasping: Theory and Experimental Validation. CoRR (2017)
Wen Sun, Arun Venkatraman, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction. CoRR (2017)
Hanzhang Hu, Debadeepta Dey, J. Andrew Bagnell, Martial Hebert
Anytime Neural Networks via Joint Optimization of Auxiliary Losses. CoRR (2017)
Katharina Mülling, Arun Venkatraman, Jean-Sebastien Valois, John Downey, Jeffrey M. Weiss, Shervin Javdani, Martial Hebert, Andrew B. Schwartz, Jennifer L. Collinger, J. Andrew Bagnell
Autonomy infused teleoperation with application to brain computer interface controlled manipulation. Auton. Robots 41 (6) (2017)
Jiaji Zhou, Robert Paolini, Aaron M. Johnson, J. Andrew Bagnell, Matthew T. Mason
A Probabilistic Planning Framework for Planar Grasping Under Uncertainty. IEEE Robotics Autom. Lett. 2 (4) (2017)
Hanzhang Hu, Debadeepta Dey, Allison Del Giorno, Martial Hebert, J. Andrew Bagnell
Log-DenseNet: How to Sparsify a DenseNet. CoRR (2017)
Allison Del Giorno, J. Andrew Bagnell, Martial Hebert
Ignoring Distractors in the Absence of Labels: Optimal Linear Projection to Remove False Positives During Anomaly Detection. CoRR (2017)
Hanzhang Hu, Wen Sun, Arun Venkatraman, Martial Hebert, J. Andrew Bagnell
Gradient Boosting on Stochastic Data Streams. AISTATS (2017)
Wen Sun, Roberto Capobianco, Geoffrey J. Gordon, J. Andrew Bagnell, Byron Boots
Learning to Smooth with Bidirectional Predictive State Inference Machines. UAI (2016)
Wen Sun, J. Andrew Bagnell
Online Bellman Residual and Temporal Difference Algorithms with Predictive Error Guarantees. IJCAI (2016)
Shreyansh Daftry, Sam Zeng, J. Andrew Bagnell, Martial Hebert
Introspective perception: Learning to predict failures in vision systems. IROS (2016)
Allison Del Giorno, J. Andrew Bagnell, Martial Hebert
A Discriminative Framework for Anomaly Detection in Large Videos. ECCV (5) (2016)
Arun Venkatraman, Wen Sun, Martial Hebert, Byron Boots, J. Andrew Bagnell
Inference Machines for Nonparametric Filter Learning. IJCAI (2016)
Shreyansh Daftry, J. Andrew Bagnell, Martial Hebert
Learning Transferable Policies for Monocular Reactive MAV Control. CoRR (2016)
Shreyansh Daftry, Sam Zeng, J. Andrew Bagnell, Martial Hebert
Introspective Perception: Learning to Predict Failures in Vision Systems. CoRR (2016)
Arun Venkatraman, Roberto Capobianco, Lerrel Pinto, Martial Hebert, Daniele Nardi, J. Andrew Bagnell
Improved Learning of Dynamics Models for Control. ISER (2016)
Wen Sun, Arun Venkatraman, Byron Boots, J. Andrew Bagnell
Learning to Filter with Predictive State Inference Machines. ICML (2016)
Allison Del Giorno, J. Andrew Bagnell, Martial Hebert
A Discriminative Framework for Anomaly Detection in Large Videos. CoRR (2016)
Hanzhang Hu, Alexander Grubb, J. Andrew Bagnell, Martial Hebert
Efficient Feature Group Sequencing for Anytime Linear Prediction. UAI (2016)
Shreyansh Daftry, J. Andrew Bagnell, Martial Hebert
Learning Transferable Policies for Monocular Reactive MAV Control. ISER (2016)
Jiaji Zhou, Robert Paolini, J. Andrew Bagnell, Matthew T. Mason
A Convex Polynomial Force-Motion Model for Planar Sliding: Identification and Application. CoRR (2016)
Arun Venkatraman, Wen Sun, Martial Hebert, J. Andrew Bagnell, Byron Boots
Online Instrumental Variable Regression with Applications to Online Linear System Identification. AAAI (2016)
Jiaji Zhou, Robert Paolini, J. Andrew Bagnell, Matthew T. Mason
A convex polynomial force-motion model for planar sliding: Identification and application. ICRA (2016)
Shreyansh Daftry, Sam Zeng, Arbaaz Khan, Debadeepta Dey, Narek Melik-Barkhudarov, J. Andrew Bagnell, Martial Hebert
Robust Monocular Flight in Cluttered Outdoor Environments. CoRR (2016)
Sanjiban Choudhury, Sebastian A. Scherer, J. Andrew Bagnell
Theoretical Limits of Speed and Resolution for Kinodynamic Planning in a Poisson Forest. Robotics: Science and Systems (2015)
Katharina Mülling, Arun Venkatraman, Jean-Sebastien Valois, John Downey, Jeffrey M. Weiss, Shervin Javdani, Martial Hebert, Andrew B. Schwartz, Jennifer L. Collinger, J. Andrew Bagnell
Autonomy Infused Teleoperation with Application to BCI Manipulation. Robotics: Science and Systems (2015)
Nicholas Rhinehart, Jiaji Zhou, Martial Hebert, J. Andrew Bagnell
Visual chunking: A list prediction framework for region-based object detection. ICRA (2015)
Debadeepta Dey, Varun Ramakrishna, Martial Hebert, J. Andrew Bagnell
Predicting Multiple Structured Visual Interpretations. ICCV (2015)
Shervin Javdani, Siddhartha S. Srinivasa, J. Andrew Bagnell
Shared Autonomy via Hindsight Optimization. Robotics: Science and Systems (2015)
Shervin Javdani, J. Andrew Bagnell, Siddhartha S. Srinivasa
Shared Autonomy via Hindsight Optimization. CoRR (2015)
Anthony Stentz, Herman Herman, Alonzo Kelly, Eric Meyhofer, G. Clark Haynes, David Stager, Brian Zajac, J. Andrew Bagnell, Jordan Brindza, Christopher M. Dellin, Michael David George, Jose Gonzalez-Mora, Sean Hyde, Morgan Jones, Michel Laverne, Maxim Likhachev, Levi Lister, Matthew Powers, Oscar Ramos, Justin Ray, David Rice, Justin Scheifflee, Raumi Sidki, Siddhartha S. Srinivasa, Kyle Strabala, Jean-Philippe Tardif, Jean-Sebastien Valois, Michael Vande Weghe, Michael Wagner, Carl Wellington
CHIMP, the CMU Highly Intelligent Mobile Platform. J. Field Robotics 32 (2) (2015)
Katharina Mülling, Arun Venkatraman, Jean-Sebastien Valois, John Downey, Jeffrey M. Weiss, Shervin Javdani, Martial Hebert, Andrew B. Schwartz, Jennifer L. Collinger, J. Andrew Bagnell
Autonomy Infused Teleoperation with Application to BCI Manipulation. CoRR (2015)
Debadeepta Dey, Kumar Shaurya Shankar, Sam Zeng, Rupesh Mehta, M. Talha Agcayazi, Christopher Eriksen, Shreyansh Daftry, Martial Hebert, J. Andrew Bagnell
Vision and Learning for Deliberative Monocular Cluttered Flight. FSR (2015)
Wen Sun, J. Andrew Bagnell
Online Bellman Residual Algorithms with Predictive Error Guarantees. UAI (2015)
Wen Sun, Arun Venkatraman, Byron Boots, J. Andrew Bagnell
Learning to Filter with Predictive State Inference Machines. CoRR (2015)
Arun Venkatraman, Martial Hebert, J. Andrew Bagnell
Improving Multi-Step Prediction of Learned Time Series Models. AAAI (2015)
Yuxin Chen, Shervin Javdani, Amin Karbasi, J. Andrew Bagnell, Siddhartha S. Srinivasa, Andreas Krause
Submodular Surrogates for Value of Information. AAAI (2015)
Anca D. Dragan, Katharina Mülling, J. Andrew Bagnell, Siddhartha S. Srinivasa
Movement primitives via optimization. ICRA (2015)
Debadeepta Dey, Kumar Shaurya Shankar, Sam Zeng, Rupesh Mehta, M. Talha Agcayazi, Christopher Eriksen, Shreyansh Daftry, Martial Hebert, J. Andrew Bagnell
Vision and Learning for Deliberative Monocular Cluttered Flight. CoRR (2014)
Nicholas Rhinehart, Jiaji Zhou, Martial Hebert, J. Andrew Bagnell
Visual Chunking: A List Prediction Framework for Region-Based Object Detection. CoRR (2014)
Dov Katz, Arun Venkatraman, Moslem Kazemi, J. Andrew Bagnell, Anthony Stentz
Perceiving, learning, and exploiting object affordances for autonomous pile manipulation. Auton. Robots 37 (4) (2014)
Kevin Waugh, Dustin Morrill, J. Andrew Bagnell, Michael Bowling
Solving Games with Functional Regret Estimation. CoRR (2014)
Moslem Kazemi, Jean-Sebastien Valois, J. Andrew Bagnell, Nancy S. Pollard
Human-inspired force compliant grasping primitives. Auton. Robots 37 (2) (2014)
Shervin Javdani, Yuxin Chen, Amin Karbasi, Andreas Krause, J. Andrew Bagnell, Siddhartha S. Srinivasa
Near Optimal Bayesian Active Learning for Decision Making. CoRR (2014)
Kevin Waugh, J. Andrew Bagnell
A Unified View of Large-scale Zero-sum Equilibrium Computation. CoRR (2014)
Hanzhang Hu, Alexander Grubb, J. Andrew Bagnell, Martial Hebert
Efficient Feature Group Sequencing for Anytime Linear Prediction. CoRR (2014)
Stéphane Ross, J. Andrew Bagnell
Reinforcement and Imitation Learning via Interactive No-Regret Learning. CoRR (2014)
Brian D. Ziebart, J. Andrew Bagnell, Anind K. Dey
The Principle of Maximum Causal Entropy for Estimating Interacting Processes. IEEE Trans. Inf. Theory 59 (4) (2013)
Jiaji Zhou, Stéphane Ross, Yisong Yue, Debadeepta Dey, J. Andrew Bagnell
Knapsack Constrained Contextual Submodular List Prediction with Application to Multi-document Summarization. CoRR (2013)
Matthew Zucker, Nathan D. Ratliff, Anca D. Dragan, Mihail Pivtoraiko, Matthew Klingensmith, Christopher M. Dellin, J. Andrew Bagnell, Siddhartha S. Srinivasa
CHOMP: Covariant Hamiltonian optimization for motion planning. Int. J. Robotics Res. 32 (9-10) (2013)
Kevin Waugh, Brian D. Ziebart, J. Andrew Bagnell
Computational Rationalization: The Inverse Equilibrium Problem. CoRR (2013)
Jens Kober, J. Andrew Bagnell, Jan Peters
Reinforcement learning in robotics: A survey. Int. J. Robotics Res. 32 (11) (2013)
David M. Blei, J. Andrew Bagnell, Andrew McCallum
Learning with Scope, with Application to Information Extraction and Classification CoRR (2013)
Alexander Grubb, Daniel Munoz, J. Andrew Bagnell, Martial Hebert
SpeedMachines: Anytime Structured Prediction. CoRR (2013)
Stéphane Ross, Jiaji Zhou, Yisong Yue, Debadeepta Dey, J. Andrew Bagnell
Learning Policies for Contextual Submodular Prediction CoRR (2013)
Dov Katz, Moslem Kazemi, J. Andrew Bagnell, Anthony Stentz
Clearing a pile of unknown objects using interactive perception. ICRA (2013)
Dov Katz, Moslem Kazemi, J. Andrew Bagnell, Anthony Stentz
Interactive segmentation, tracking, and kinematic modeling of unknown 3D articulated objects. ICRA (2013)
Hanzhang Hu, Daniel Munoz, J. Andrew Bagnell, Martial Hebert
Efficient 3-D scene analysis from streaming data. ICRA (2013)

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Publication Activity (10 Years)

Top Topics

Top Venues

J. Andrew Bagnell