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Doina Precup, Ph.D. - Publications

Affiliations: 
2000 University of Massachusetts, Amherst, Amherst, MA 
Area:
Reinforcement Learning
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52 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2022 Matsuo Y, LeCun Y, Sahani M, Precup D, Silver D, Sugiyama M, Uchibe E, Morimoto J. Deep learning, reinforcement learning, and world models. Neural Networks : the Official Journal of the International Neural Network Society. 152: 267-275. PMID 35569196 DOI: 10.1016/j.neunet.2022.03.037  0.667
2020 Barreto A, Hou S, Borsa D, Silver D, Precup D. Fast reinforcement learning with generalized policy updates. Proceedings of the National Academy of Sciences of the United States of America. PMID 32817541 DOI: 10.1073/Pnas.1907370117  0.677
2020 Wu D, Wang B, Precup D, Boulet B. Multiple Kernel Learning-Based Transfer Regression for Electric Load Forecasting Ieee Transactions On Smart Grid. 11: 1183-1192. DOI: 10.1109/Tsg.2019.2933413  0.502
2019 Khetarpal K, Precup D. Learning Options with Interest Functions Proceedings of the Aaai Conference On Artificial Intelligence. 33: 9955-9956. DOI: 10.1609/aaai.v33i01.33019955  0.489
2019 Lupu A, Durand A, Precup D. Leveraging Observations in Bandits: Between Risks and Benefits Proceedings of the Aaai Conference On Artificial Intelligence. 33: 6112-6119. DOI: 10.1609/AAAI.V33I01.33016112  0.348
2019 Francois-Lavet V, Bengio Y, Precup D, Pineau J. Combined Reinforcement Learning via Abstract Representations Proceedings of the Aaai Conference On Artificial Intelligence. 33: 3582-3589. DOI: 10.1609/aaai.v33i01.33013582  0.423
2018 Bacon P, Precup D. Constructing Temporal Abstractions Autonomously in Reinforcement Learning Ai Magazine. 39: 39-50. DOI: 10.1609/Aimag.V39I1.2780  0.558
2015 Jafarpour N, Izadi M, Precup D, Buckeridge DL. Quantifying the determinants of outbreak detection performance through simulation and machine learning. Journal of Biomedical Informatics. 53: 180-7. PMID 25445482 DOI: 10.1016/J.Jbi.2014.10.009  0.341
2015 Mann TA, Mannor S, Precup D. Approximate value iteration with temporally extended actions Journal of Artificial Intelligence Research. 53: 375-438. DOI: 10.1613/Jair.4676  0.381
2015 Farahmand AM, Precup D, Barreto AMS, Ghavamzadeh M. Classification-based approximate policy iteration Ieee Transactions On Automatic Control. 60: 2989-2993. DOI: 10.1109/Tac.2015.2418411  0.384
2015 Bacon PL, Balle B, Precup D. Learning and planning with timing information in Markov decision processes Uncertainty in Artificial Intelligence - Proceedings of the 31st Conference, Uai 2015. 111-120.  0.352
2014 Barreto AMS, Pineau J, Precup D. Policy iteration based on stochastic factorization Journal of Artificial Intelligence Research. 50: 763-803. DOI: 10.1613/Jair.4301  0.301
2014 McCarthy SM, Precup D. Theoretical results on the effect of 'shortcut' actions in MDPs Connection Science. 26: 179-193. DOI: 10.1080/09540091.2014.885304  0.306
2014 Bachman P, Alsharif O, Precup D. Learning with pseudo-ensembles Advances in Neural Information Processing Systems. 4: 3365-3373.  0.478
2014 Sutton RS, Mahmood AR, Precup D, Van Hasselt H. A new Q(λ) with interim forward view and Monte Carlo equivalence 31st International Conference On Machine Learning, Icml 2014. 3: 1973-1988.  0.357
2013 Frank J, Mannor S, Pineau J, Precup D. Time Series Analysis Using Geometric Template Matching. Ieee Transactions On Pattern Analysis and Machine Intelligence. 35: 740-54. PMID 22641699 DOI: 10.1109/Tpami.2012.121  0.332
2013 Gehring C, Precup D. Smart exploration in reinforcement learning using absolute temporal difference errors 12th International Conference On Autonomous Agents and Multiagent Systems 2013, Aamas 2013. 2: 1037-1043.  0.389
2013 Kim B, Farahmand AM, Pineau J, Precup D. Learning from limited demonstrations Advances in Neural Information Processing Systems.  0.396
2012 Still S, Precup D. An information-theoretic approach to curiosity-driven reinforcement learning. Theory in Biosciences = Theorie in Den Biowissenschaften. 131: 139-48. PMID 22791268 DOI: 10.1007/S12064-011-0142-Z  0.43
2012 Agmon N, Agrawal V, Aha DW, Aloimonos Y, Buckley D, Doshi P, Geib C, Grasso F, Green N, Johnston B, Kaliski B, Kiekintveld C, Law E, Lieberman H, Mengshoel OJ, ... ... Precup D, et al. Reports of the AAAI 2011 conference workshops Ai Magazine. 33: 57-70. DOI: 10.1609/Aimag.V33I1.2390  0.314
2012 Castro PS, Precup D. Automatic construction of temporally extended actions for MDPs using bisimulation metrics Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7188: 140-152. DOI: 10.1007/978-3-642-29946-9_16  0.371
2012 Barreto AMS, Precup D, Pineau J. On-line reinforcement learning using incremental kernel-based stochastic factorization Advances in Neural Information Processing Systems. 2: 1484-1492.  0.344
2012 Farahmand AM, Precup D. Value pursuit iteration Advances in Neural Information Processing Systems. 2: 1340-1348.  0.317
2012 Warrick PA, Hamilton EF, Kearney RE, Precup D. A machine-learning approach to the detection of fetal hypoxia during labor and delivery Ai Magazine. 33: 79-90.  0.316
2011 Sutton RS, Modayil J, Degris MDT, Pilarski PM, White A, Precup D. Horde: A scalable real-time architecture for learning knowledge from unsupervised sensorimotor interaction 10th International Conference On Autonomous Agents and Multiagent Systems 2011, Aamas 2011. 2: 713-720.  0.58
2011 Barreto AMS, Precup D, Pineau J. Reinforcement learning using kernel-based stochastic factorization Advances in Neural Information Processing Systems 24: 25th Annual Conference On Neural Information Processing Systems 2011, Nips 2011.  0.456
2011 Bachman P, Precup D. Learning compact representations of time-varying processes Proceedings of the National Conference On Artificial Intelligence. 2: 1748-1749.  0.436
2010 Andrews S, Kry P, Precup D. Learning control policies for virtual grasping applications Ceur Workshop Proceedings. 588: 12-14.  0.363
2010 Warrick PA, Hamilton EF, Kearney RE, Precup D. A machine learning approach to the detection of fetal hypoxia during labor and delivery Proceedings of the National Conference On Artificial Intelligence. 3: 1865-1870.  0.316
2010 Dinculescu M, Precup D. Approximate predictive representations of partially observable systems Icml 2010 - Proceedings, 27th International Conference On Machine Learning. 895-902.  0.376
2010 Comanici G, Precup D. Optimal policy switching algorithms for reinforcement learning Proceedings of the International Joint Conference On Autonomous Agents and Multiagent Systems, Aamas. 2: 709-714.  0.405
2009 Sutton RS, Maei HR, Precup D, Bhatnagar S, Silver D, Szepesvári C, Wiewiora E. Fast gradient-descent methods for temporal-difference learning with linear function approximation Proceedings of the 26th International Conference On Machine Learning, Icml 2009. 993-1000. DOI: 10.1145/1553374.1553501  0.725
2009 Zhioua S, Precup D, Laviolette F, Desharnais J. Learning the difference between partially observable dynamical systems Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5782: 664-677. DOI: 10.1007/978-3-642-04174-7_43  0.381
2009 Sutton RS, Maei HR, Precup D, Bhatnagar S, Silver D, Szepesvári C, Wiewiora E. Fast gradient-descent methods for temporal-difference learning with linear function approximation Proceedings of the 26th International Conference On Machine Learning, Icml 2009. 993-1000.  0.757
2009 Maei HR, Szepesvari C, Bhatnagar S, Precup D, Silver D, Sutton RS. Convergent temporal-difference learning with arbitrary smooth function approximation Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference. 1204-1212.  0.753
2008 Brooks R, Arbel T, Precup D. Anytime similarity measures for faster alignment Computer Vision and Image Understanding. 110: 378-389. DOI: 10.1016/J.Cviu.2007.09.011  0.304
2008 Frank J, Mannor S, Precup D. Reinforcement learning in the presence of rare events Proceedings of the 25th International Conference On Machine Learning. 336-343.  0.442
2006 Keller PW, Mannor S, Precup D. Automatic basis function construction for approximate dynamic programming and reinforcement learning Acm International Conference Proceeding Series. 148: 449-456. DOI: 10.1145/1143844.1143901  0.349
2006 Izadi MT, Precup D, Azar D. Belief selection in point-based planning algorithms for POMDPs Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4013: 383-394. DOI: 10.1007/11766247_33  0.3
2006 Gavaldà R, Keller PW, Pineau J, Precup D. PAC-learning of Markov Models with Hidden State Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4212: 150-161.  0.427
2005 Muslea I, Dignum V, Corkill D, Jonker C, Dignum F, Coradeschi S, Saffiotti A, Fu D, Orkin J, Cheetham W, Goebel K, Bonissone P, Soh LK, Jones RM, Wray RE, ... ... Precup D, et al. The workshop program at the Nineteenth National Conference on Artificial Intelligence Ai Magazine. 26: 103-108. DOI: 10.1609/Aimag.V26I1.1806  0.373
2005 Precup D, Sutton RS, Paduraru C, Koop A, Singh S. Off-policy learning with options and recognizers Advances in Neural Information Processing Systems. 1097-1104.  0.583
2004 Ratitch B, Mahadevan S, Precup D. Sparse distributed memories in reinforcement learning: Case studies Aaai Workshop - Technical Report. 85-90.  0.329
2003 Ratitch B, Precup D. Using MDP characteristics to guide exploration in reinforcement learning Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). 2837: 313-324.  0.411
2003 Rivest F, Precup D. Combining TD-learning with Cascade-correlation Networks Proceedings, Twentieth International Conference On Machine Learning. 2: 632-639.  0.35
2002 LETIA IA, PRECUP D. ERRATUM: DEVELOPING COLLABORATIVE GOLOG AGENTS BY REINFORCEMENT LEARNING International Journal On Artificial Intelligence Tools. 11: 473-473. DOI: 10.1142/S021821300200099X  0.412
2002 Ratitch B, Precup D. Characterizing Markov decision processes Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2430: 391-404.  0.393
2002 Stolle M, Precup D. Learning options in reinforcement learning Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2371: 212-223.  0.379
2001 Letia IA, Precup D. Developing collaborative Golog agents by reinforcement learning Proceedings of the International Conference On Tools With Artificial Intelligence. 195-202. DOI: 10.1142/S0218213002000873  0.397
1999 Sutton RS, Precup D, Singh S. Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning Artificial Intelligence. 112: 181-211. DOI: 10.1016/S0004-3702(99)00052-1  0.668
1999 Sutton RS, Singh S, Precup D, Ravindran B. Improved switching among temporally abstract actions Advances in Neural Information Processing Systems. 1066-1072.  0.399
1998 Precup D, Sutton RS. Multi-time models for temporally abstract planning Advances in Neural Information Processing Systems. 1050-1056.  0.423
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