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Geoffrey J. Gordon
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- affiliation: Machine Learning Department, Carnegie Mellon University
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2020 – today
- 2024
- [c116]My Phan, Kianté Brantley, Stephanie Milani, Soroush Mehri, Gokul Swamy, Geoffrey J. Gordon:
When is Transfer Learning Possible? ICML 2024 - [i51]Shiva Kaul, Geoffrey J. Gordon:
Meta-Analysis with Untrusted Data. CoRR abs/2407.09387 (2024) - [i50]Zhuorui Ye, Stephanie Milani, Geoffrey J. Gordon, Fei Fang:
Concept-Based Interpretable Reinforcement Learning with Limited to No Human Labels. CoRR abs/2407.15786 (2024) - 2022
- [j17]Han Zhao, Geoffrey J. Gordon:
Inherent Tradeoffs in Learning Fair Representations. J. Mach. Learn. Res. 23: 57:1-57:26 (2022) - [j16]Han Zhao, Chen Dan, Bryon Aragam, Tommi S. Jaakkola, Geoffrey J. Gordon, Pradeep Ravikumar:
Fundamental Limits and Tradeoffs in Invariant Representation Learning. J. Mach. Learn. Res. 23: 340:1-340:49 (2022) - 2021
- [c115]Kianté Brantley, Soroush Mehri, Geoffrey J. Gordon:
Successor Feature Sets: Generalizing Successor Representations Across Policies. AAAI 2021: 11774-11781 - [c114]Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon, Han Zhao:
Understanding and Mitigating Accuracy Disparity in Regression. ICML 2021: 1866-1876 - [c113]Peiyuan Liao, Han Zhao, Keyulu Xu, Tommi S. Jaakkola, Geoffrey J. Gordon, Stefanie Jegelka, Ruslan Salakhutdinov:
Information Obfuscation of Graph Neural Networks. ICML 2021: 6600-6610 - [c112]Alessandro Sordoni, Nouha Dziri, Hannes Schulz, Geoffrey J. Gordon, Philip Bachman, Remi Tachet des Combes:
Decomposed Mutual Information Estimation for Contrastive Representation Learning. ICML 2021: 9859-9869 - [i49]Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon, Han Zhao:
Understanding and Mitigating Accuracy Disparity in Regression. CoRR abs/2102.12013 (2021) - [i48]Kianté Brantley, Soroush Mehri, Geoffrey J. Gordon:
Successor Feature Sets: Generalizing Successor Representations Across Policies. CoRR abs/2103.02650 (2021) - [i47]Alessandro Sordoni, Nouha Dziri, Hannes Schulz, Geoffrey J. Gordon, Philip Bachman, Remi Tachet des Combes:
Decomposed Mutual Information Estimation for Contrastive Representation Learning. CoRR abs/2106.13401 (2021) - 2020
- [c111]Ching-An Cheng, Remi Tachet des Combes, Byron Boots, Geoffrey J. Gordon:
A Reduction from Reinforcement Learning to No-Regret Online Learning. AISTATS 2020: 3514-3524 - [c110]Sandesh Adhikary, Siddarth Srinivasan, Geoffrey J. Gordon, Byron Boots:
Expressiveness and Learning of Hidden Quantum Markov Models. AISTATS 2020: 4151-4161 - [c109]Renato Negrinho, Matthew R. Gormley, Geoffrey J. Gordon:
An Empirical Investigation of Beam-Aware Training in Supertagging. EMNLP (Findings) 2020: 4534-4542 - [c108]Han Zhao, Amanda Coston, Tameem Adel, Geoffrey J. Gordon:
Conditional Learning of Fair Representations. ICLR 2020 - [c107]Han Zhao, Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon:
Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation. NeurIPS 2020 - [c106]Remi Tachet des Combes, Han Zhao, Yu-Xiang Wang, Geoffrey J. Gordon:
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift. NeurIPS 2020 - [i46]Remi Tachet des Combes, Han Zhao, Yu-Xiang Wang, Geoffrey J. Gordon:
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift. CoRR abs/2003.04475 (2020) - [i45]Peiyuan Liao, Han Zhao, Keyulu Xu, Tommi S. Jaakkola, Geoffrey J. Gordon, Stefanie Jegelka, Ruslan Salakhutdinov:
Graph Adversarial Networks: Protecting Information against Adversarial Attacks. CoRR abs/2009.13504 (2020) - [i44]Renato Negrinho, Matthew R. Gormley, Geoffrey J. Gordon:
An Empirical Investigation of Beam-Aware Training in Supertagging. CoRR abs/2010.04980 (2020) - [i43]Han Zhao, Chen Dan, Bryon Aragam, Tommi S. Jaakkola, Geoffrey J. Gordon, Pradeep Ravikumar:
Fundamental Limits and Tradeoffs in Invariant Representation Learning. CoRR abs/2012.10713 (2020)
2010 – 2019
- 2019
- [c105]Han Zhao, Junjie Hu, Zhenyao Zhu, Adam Coates, Geoffrey J. Gordon:
Deep Generative and Discriminative Domain Adaptation. AAMAS 2019: 2315-2317 - [c104]Mariya Toneva, Alessandro Sordoni, Remi Tachet des Combes, Adam Trischler, Yoshua Bengio, Geoffrey J. Gordon:
An Empirical Study of Example Forgetting during Deep Neural Network Learning. ICLR (Poster) 2019 - [c103]Han Zhao, Remi Tachet des Combes, Kun Zhang, Geoffrey J. Gordon:
On Learning Invariant Representations for Domain Adaptation. ICML 2019: 7523-7532 - [c102]Han Zhao, Yao-Hung Hubert Tsai, Ruslan Salakhutdinov, Geoffrey J. Gordon:
Learning Neural Networks with Adaptive Regularization. NeurIPS 2019: 11389-11400 - [c101]Renato Negrinho, Matthew R. Gormley, Geoffrey J. Gordon, Darshan Patil, Nghia Le, Daniel Ferreira:
Towards modular and programmable architecture search. NeurIPS 2019: 13715-13725 - [c100]Han Zhao, Geoffrey J. Gordon:
Inherent Tradeoffs in Learning Fair Representations. NeurIPS 2019: 15649-15659 - [c99]Han Zhao, Otilia Stretcu, Alexander J. Smola, Geoffrey J. Gordon:
Efficient Multitask Feature and Relationship Learning. UAI 2019: 777-787 - [i42]Han Zhao, Remi Tachet des Combes, Kun Zhang, Geoffrey J. Gordon:
On Learning Invariant Representation for Domain Adaptation. CoRR abs/1901.09453 (2019) - [i41]Han Zhao, Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon:
Adversarial Task-Specific Privacy Preservation under Attribute Attack. CoRR abs/1906.07902 (2019) - [i40]Han Zhao, Geoffrey J. Gordon:
Inherent Tradeoffs in Learning Fair Representation. CoRR abs/1906.08386 (2019) - [i39]Han Zhao, Yao-Hung Hubert Tsai, Ruslan Salakhutdinov, Geoffrey J. Gordon:
Learning Neural Networks with Adaptive Regularization. CoRR abs/1907.06288 (2019) - [i38]Renato Negrinho, Darshan Patil, Nghia Le, Daniel Ferreira, Matthew R. Gormley, Geoffrey J. Gordon:
Towards modular and programmable architecture search. CoRR abs/1909.13404 (2019) - [i37]Han Zhao, Amanda Coston, Tameem Adel, Geoffrey J. Gordon:
Conditional Learning of Fair Representations. CoRR abs/1910.07162 (2019) - [i36]Ching-An Cheng, Remi Tachet des Combes, Byron Boots, Geoffrey J. Gordon:
A Reduction from Reinforcement Learning to No-Regret Online Learning. CoRR abs/1911.05873 (2019) - [i35]Sandesh Adhikary, Siddarth Srinivasan, Geoffrey J. Gordon, Byron Boots:
Expressiveness and Learning of Hidden Quantum Markov Models. CoRR abs/1912.02098 (2019) - 2018
- [j15]Bohan Zhang, Dana Van Aken, Justin Wang, Tao Dai, Shuli Jiang, Jacky Lao, Siyuan Sheng, Andrew Pavlo, Geoffrey J. Gordon:
A Demonstration of the OtterTune Automatic Database Management System Tuning Service. Proc. VLDB Endow. 11(12): 1910-1913 (2018) - [c98]Ahmed Hefny, Carlton Downey, Geoffrey J. Gordon:
An Efficient, Expressive and Local Minima-Free Method for Learning Controlled Dynamical Systems. AAAI 2018: 3191-3198 - [c97]Siddarth Srinivasan, Geoffrey J. Gordon, Byron Boots:
Learning Hidden Quantum Markov Models. AISTATS 2018: 1979-1987 - [c96]Han Zhao, Shanghang Zhang, Guanhang Wu, João Paulo Costeira, José M. F. Moura, Geoffrey J. Gordon:
Multiple Source Domain Adaptation with Adversarial Learning. ICLR (Workshop) 2018 - [c95]Ahmed Hefny, Zita Marinho, Wen Sun, Siddhartha S. Srinivasa, Geoffrey J. Gordon:
Recurrent Predictive State Policy Networks. ICML 2018: 1954-1963 - [c94]Wen Sun, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell:
Dual Policy Iteration. NeurIPS 2018: 7059-7069 - [c93]Han Zhao, Shanghang Zhang, Guanhang Wu, José M. F. Moura, João Paulo Costeira, Geoffrey J. Gordon:
Adversarial Multiple Source Domain Adaptation. NeurIPS 2018: 8568-8579 - [c92]Renato Negrinho, Matthew R. Gormley, Geoffrey J. Gordon:
Learning Beam Search Policies via Imitation Learning. NeurIPS 2018: 10675-10684 - [c91]Lin Ma, Dana Van Aken, Ahmed Hefny, Gustavo Mezerhane, Andrew Pavlo, Geoffrey J. Gordon:
Query-based Workload Forecasting for Self-Driving Database Management Systems. SIGMOD Conference 2018: 631-645 - [c90]Han Zhao, Geoffrey J. Gordon:
Frank-Wolfe Optimization for Symmetric-NMF under Simplicial Constraint. UAI 2018: 124-134 - [i34]Ahmed Hefny, Zita Marinho, Wen Sun, Siddhartha S. Srinivasa, Geoffrey J. Gordon:
Recurrent Predictive State Policy Networks. CoRR abs/1803.01489 (2018) - [i33]Wen Sun, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell:
Dual Policy Iteration. CoRR abs/1805.10755 (2018) - [i32]Renato Negrinho, Matthew R. Gormley, Geoffrey J. Gordon:
Learning Beam Search Policies via Imitation Learning. CoRR abs/1811.00512 (2018) - [i31]Mariya Toneva, Alessandro Sordoni, Remi Tachet des Combes, Adam Trischler, Yoshua Bengio, Geoffrey J. Gordon:
An Empirical Study of Example Forgetting during Deep Neural Network Learning. CoRR abs/1812.05159 (2018) - 2017
- [c89]Wen Sun, Arun Venkatraman, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell:
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction. ICML 2017: 3309-3318 - [c88]Carlton Downey, Ahmed Hefny, Byron Boots, Geoffrey J. Gordon, Boyue Li:
Predictive State Recurrent Neural Networks. NIPS 2017: 6053-6064 - [c87]Han Zhao, Geoffrey J. Gordon:
Linear Time Computation of Moments in Sum-Product Networks. NIPS 2017: 6894-6903 - [c86]Dana Van Aken, Andrew Pavlo, Geoffrey J. Gordon, Bohan Zhang:
Automatic Database Management System Tuning Through Large-scale Machine Learning. SIGMOD Conference 2017: 1009-1024 - [i30]Carlton Downey, Ahmed Hefny, Geoffrey J. Gordon:
Practical Learning of Predictive State Representations. CoRR abs/1702.04121 (2017) - [i29]Han Zhao, Otilia Stretcu, Renato Negrinho, Alexander J. Smola, Geoffrey J. Gordon:
Efficient Multi-task Feature and Relationship Learning. CoRR abs/1702.04423 (2017) - [i28]Han Zhao, Geoffrey J. Gordon:
Efficient Computation of Moments in Sum-Product Networks. CoRR abs/1702.04767 (2017) - [i27]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) - [i26]Renato Negrinho, Geoffrey J. Gordon:
DeepArchitect: Automatically Designing and Training Deep Architectures. CoRR abs/1704.08792 (2017) - [i25]Han Zhao, Zhenyao Zhu, Junjie Hu, Adam Coates, Geoffrey J. Gordon:
Principled Hybrids of Generative and Discriminative Domain Adaptation. CoRR abs/1705.09011 (2017) - [i24]Han Zhao, Shanghang Zhang, Guanhang Wu, João Paulo Costeira, José M. F. Moura, Geoffrey J. Gordon:
Multiple Source Domain Adaptation with Adversarial Training of Neural Networks. CoRR abs/1705.09684 (2017) - [i23]Han Zhao, Geoffrey J. Gordon:
Frank-Wolfe Optimization for Symmetric-NMF under Simplicial Constraint. CoRR abs/1706.06348 (2017) - [i22]Gilwoo Lee, Zita Marinho, Aaron M. Johnson, Geoffrey J. Gordon, Siddhartha S. Srinivasa, Matthew T. Mason:
Unsupervised Learning for Nonlinear PieceWise Smooth Hybrid Systems. CoRR abs/1710.00440 (2017) - 2016
- [c85]Han Zhao, Tameem Adel, Geoffrey J. Gordon, Brandon Amos:
Collapsed Variational Inference for Sum-Product Networks. ICML 2016: 1310-1318 - [c84]Mohammad Hassan Falakmasir, José P. González-Brenes, Geoffrey J. Gordon, Kristen E. DiCerbo:
A Data-Driven Approach for Inferring Student Proficiency from Game Activity Logs. L@S 2016: 341-349 - [c83]Han Zhao, Pascal Poupart, Geoffrey J. Gordon:
A Unified Approach for Learning the Parameters of Sum-Product Networks. NIPS 2016: 433-441 - [c82]Zita Marinho, Byron Boots, Anca D. Dragan, Arunkumar Byravan, Geoffrey J. Gordon, Siddhartha S. Srinivasa:
Functional Gradient Motion Planning in Reproducing Kernel Hilbert Spaces. Robotics: Science and Systems 2016 - [c81]Wen Sun, Roberto Capobianco, Geoffrey J. Gordon, J. Andrew Bagnell, Byron Boots:
Learning to Smooth with Bidirectional Predictive State Inference Machines. UAI 2016 - [i21]Han Zhao, Pascal Poupart, Geoffrey J. Gordon:
A Unified Approach for Learning the Parameters of Sum-Product Networks. CoRR abs/1601.00318 (2016) - [i20]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) - 2015
- [c80]Ahmed Hefny, Carlton Downey, Geoffrey J. Gordon:
Supervised Learning for Dynamical System Learning. NIPS 2015: 1963-1971 - [i19]Ahmed Hefny, Carlton Downey, Geoffrey J. Gordon:
A New View of Predictive State Methods for Dynamical System Learning. CoRR abs/1505.05310 (2015) - 2014
- [j14]Khalil Ghorbal, Jean-Baptiste Jeannin, Erik Zawadzki, André Platzer, Geoffrey J. Gordon, Peter Capell:
Hybrid Theorem Proving of Aerospace Systems: Applications and Challenges. J. Aerosp. Inf. Syst. 11(10): 702-713 (2014) - [c79]Ahmed Hefny, Robert E. Kass, Sanjeev Khanna, Matthew A. Smith, Geoffrey J. Gordon:
Fast and Improved SLEX Analysis of High-Dimensional Time Series. MLINI@NIPS 2014: 94-103 - 2013
- [c78]Michael Yudelson, Kenneth R. Koedinger, Geoffrey J. Gordon:
Individualized Bayesian Knowledge Tracing Models. AIED 2013: 171-180 - [c77]Anika Gupta, Katia P. Sycara, Geoffrey J. Gordon, Ahmed Hefny:
Exploring friend's influence in cultures in Twitter. ASONAM 2013: 584-591 - [c76]Mohammad Hassan Falakmasir, Zachary A. Pardos, Geoffrey J. Gordon, Peter Brusilovsky:
A Spectral Learning Approach to Knowledge Tracing. EDM 2013: 28-34 - [c75]Byron Boots, Geoffrey J. Gordon:
A Spectral Learning Approach to Range-Only SLAM. ICML (1) 2013: 19-26 - [c74]Erik Peter Zawadzki, André Platzer, Geoffrey J. Gordon:
A Generalization of SAT and #SAT for Robust Policy Evaluation. IJCAI 2013: 2583-2590 - [c73]Byron Boots, Geoffrey J. Gordon, Arthur Gretton:
Hilbert Space Embeddings of Predictive State Representations. UAI 2013 - [i18]Carlos Guestrin, Geoffrey J. Gordon:
Distributed Planning in Hierarchical Factored MDPs. CoRR abs/1301.0571 (2013) - [i17]Geoffrey J. Gordon:
Galerkin Methods for Complementarity Problems and Variational Inequalities. CoRR abs/1306.4753 (2013) - [i16]Byron Boots, Geoffrey J. Gordon, Arthur Gretton:
Hilbert Space Embeddings of Predictive State Representations. CoRR abs/1309.6819 (2013) - 2012
- [c72]Pradeep Varakantham, Shih-Fen Cheng, Geoffrey J. Gordon, Asrar Ahmed:
Decision Support for Agent Populations in Uncertain and Congested Environments. AAAI 2012: 1471-1477 - [c71]Geoffrey J. Gordon, Pradeep Varakantham, William Yeoh, Hoong Chuin Lau, Ajay S. Aravamudhan, Shih-Fen Cheng:
Lagrangian relaxation for large-scale multi-agent planning. AAMAS 2012: 1227-1228 - [c70]Brian D. Ziebart, Miroslav Dudík, Geoffrey J. Gordon, Katia P. Sycara, Wendi L. Adair, Jeanne M. Brett:
Identifying Culture and Leveraging Cultural Differences for Negotiation Agents. HICSS 2012: 618-627 - [c69]Geoffrey J. Gordon, Pradeep Varakantham, William Yeoh, Hoong Chuin Lau, Ajay S. Aravamudhan, Shih-Fen Cheng:
Lagrangian Relaxation for Large-Scale Multi-agent Planning. IAT 2012: 494-501 - [c68]Byron Boots, Geoffrey J. Gordon:
Two Manifold Problems with Applications to Nonlinear System Identification. ICML 2012 - [i15]Ajit Paul Singh, Geoffrey J. Gordon:
A Bayesian Matrix Factorization Model for Relational Data. CoRR abs/1203.3517 (2012) - [i14]Geoffrey J. Gordon, Sue Ann Hong, Miroslav Dudík:
First-Order Mixed Integer Linear Programming. CoRR abs/1205.2644 (2012) - [i13]Miroslav Dudík, Geoffrey J. Gordon:
A Sampling-Based Approach to Computing Equilibria in Succinct Extensive-Form Games. CoRR abs/1205.2649 (2012) - [i12]Byron Boots, Geoffrey J. Gordon:
Two-Manifold Problems with Applications to Nonlinear System Identification. CoRR abs/1206.4648 (2012) - [i11]Byron Boots, Geoffrey J. Gordon:
A Spectral Learning Approach to Range-Only SLAM. CoRR abs/1207.2491 (2012) - [i10]Matthew Rosencrantz, Geoffrey J. Gordon, Sebastian Thrun:
Decentralized Sensor Fusion With Distributed Particle Filters. CoRR abs/1212.2493 (2012) - [i9]Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun:
Policy-contingent abstraction for robust robot control. CoRR abs/1212.2495 (2012) - [i8]Geoffrey J. Gordon:
Fast Solutions to Projective Monotone Linear Complementarity Problems. CoRR abs/1212.6958 (2012) - 2011
- [j13]Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon:
Closing the learning-planning loop with predictive state representations. Int. J. Robotics Res. 30(7): 954-966 (2011) - [c67]Byron Boots, Geoffrey J. Gordon:
An Online Spectral Learning Algorithm for Partially Observable Nonlinear Dynamical Systems. AAAI 2011: 293-300 - [c66]Min Chi, Kenneth R. Koedinger, Geoffrey J. Gordon, Pamela W. Jordan, Kurt VanLehn:
Instructional Factors Analysis: A Cognitive Model For Multiple Instructional Interventions. EDM 2011: 61-70 - [c65]Anca D. Dragan, Geoffrey J. Gordon, Siddhartha S. Srinivasa:
Learning from Experience in Manipulation Planning: Setting the Right Goals. ISRR 2011: 309-326 - [c64]Geoffrey J. Gordon, David B. Dunson:
Preface. AISTATS 2011: 1-2 - [c63]Sue Ann Hong, Geoffrey J. Gordon:
Optimal Distributed Market-Based Planning for Multi-Agent Systems with Shared Resources. AISTATS 2011: 351-360 - [c62]Stéphane Ross, Geoffrey J. Gordon, Drew Bagnell:
A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning. AISTATS 2011: 627-635 - [c61]Erik Zawadzki, Geoffrey J. Gordon, André Platzer:
An Instantiation-Based Theorem Prover for First-Order Programming. AISTATS 2011: 855-863 - [e1]Geoffrey J. Gordon, David B. Dunson, Miroslav Dudík:
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2011, Fort Lauderdale, USA, April 11-13, 2011. JMLR Proceedings 15, JMLR.org 2011 [contents] - [i7]Geoffrey J. Gordon, Nicholas Roy, Sebastian Thrun:
Finding Approximate POMDP solutions Through Belief Compression. CoRR abs/1107.0053 (2011) - [i6]Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun:
Anytime Point-Based Approximations for Large POMDPs. CoRR abs/1110.0027 (2011) - [i5]Byron Boots, Geoffrey J. Gordon:
Two-Manifold Problems. CoRR abs/1112.6399 (2011) - 2010
- [j12]Peng Yang, Randy A. Freeman, Geoffrey J. Gordon, Kevin M. Lynch, Siddhartha S. Srinivasa, Rahul Sukthankar:
Decentralized estimation and control of graph connectivity for mobile sensor networks. Autom. 46(2): 390-396 (2010) - [c60]Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon:
Closing the learning-planning loop with predictive state representations. AAMAS 2010: 1369-1370 - [c59]Julian Ramos, Sajid M. Siddiqi, Artur Dubrawski, Geoffrey J. Gordon, Abhishek Sharma:
Automatic state discovery for unstructured audio scene classification. ICASSP 2010: 2154-2157 - [c58]Le Song, Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon, Alexander J. Smola:
Hilbert Space Embeddings of Hidden Markov Models. ICML 2010: 991-998 - [c57]Byron Boots, Geoffrey J. Gordon:
Predictive State Temporal Difference Learning. NIPS 2010: 271-279 - [c56]Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon:
Closing the Learning-Planning Loop with Predictive State Representations. Robotics: Science and Systems 2010 - [c55]Ajit Paul Singh, Geoffrey J. Gordon:
A Bayesian Matrix Factorization Model for Relational Data. UAI 2010: 556-563 - [c54]Sajid M. Siddiqi, Byron Boots, Geoffrey J. Gordon:
Reduced-Rank Hidden Markov Models. AISTATS 2010: 741-748 - [i4]Byron Boots, Geoffrey J. Gordon:
Predictive State Temporal Difference Learning. CoRR abs/1011.0041 (2010) - [i3]Stéphane Ross, Geoffrey J. Gordon, J. Andrew Bagnell:
No-Regret Reductions for Imitation Learning and Structured Prediction. CoRR abs/1011.0686 (2010)
2000 – 2009
- 2009
- [c53]Miroslav Dudík, Geoffrey J. Gordon:
A Sampling-Based Approach to Computing Equilibria in Succinct Extensive-Form Games. UAI 2009: 151-160 - [c52]Geoffrey J. Gordon, Sue Ann Hong, Miroslav Dudík:
First-Order Mixed Integer Linear Programming. UAI 2009: 213-222 - [c51]Thomas S. Stepleton, Zoubin Ghahramani, Geoffrey J. Gordon, Tai Sing Lee:
The Block Diagonal Infinite Hidden Markov Model. AISTATS 2009: 552-559 - [i2]Sajid M. Siddiqi, Byron Boots, Geoffrey J. Gordon:
Reduced-Rank Hidden Markov Models. CoRR abs/0910.0902 (2009) - [i1]