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Sridhar Mahadevan Vis

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*2009
61EEKimberly Ferguson, Beverly Park Woolf, Sridhar Mahadevan: Transfer Learning and Representation Discovery in Intelligent Tutoring Systems. AIED 2009: 605-607
60EEJeffrey Johns, Marek Petrik, Sridhar Mahadevan: Hybrid Least-Squares Algorithms for Approximate Policy Evaluation. ECML/PKDD (1) 2009: 9
59EEChang Wang, Sridhar Mahadevan: Manifold Alignment without Correspondence. IJCAI 2009: 1273-1278
58EEChang Wang, Sridhar Mahadevan: Multiscale Analysis of Document Corpora Based on Diffusion Models. IJCAI 2009: 1592-1597
57EESridhar Mahadevan: Learning Representation and Control in Markov Decision Processes: New Frontiers. Foundations and Trends in Machine Learning 1(4): 403-565 (2009)
2008
56 Sridhar Mahadevan: Fast Spectral Learning using Lanczos Eigenspace Projections. AAAI 2008: 1472-1475
55EEChang Wang, Sridhar Mahadevan: Manifold alignment using Procrustes analysis. ICML 2008: 1120-1127
2007
54 Jeffrey Johns, Sridhar Mahadevan, Chang Wang: Compact Spectral Bases for Value Function Approximation Using Kronecker Factorization. AAAI 2007: 559-564
53 Ivon Arroyo, Kimberly Ferguson, Jeffrey Johns, Toby Dragon, Hasmik Meheranian, Don Fisher, Andrew G. Barto, Sridhar Mahadevan, Beverly Park Woolf: Repairing Disengagement With Non-Invasive Interventions. AIED 2007: 195-202
52 Sridhar Mahadevan, Sarah Osentoski, Jeffrey Johns, Kimberly Ferguson, Chang Wang: Learning to Plan Using Harmonic Analysis of Diffusion Models. ICAPS 2007: 224-231
51EEJeffrey Johns, Sridhar Mahadevan: Constructing basis functions from directed graphs for value function approximation. ICML 2007: 385-392
50EESridhar Mahadevan: Adaptive mesh compression in 3D computer graphics using multiscale manifold learning. ICML 2007: 585-592
49EESarah Osentoski, Sridhar Mahadevan: Learning state-action basis functions for hierarchical MDPs. ICML 2007: 705-712
2006
48 Sridhar Mahadevan, Mauro Maggioni, Kimberly Ferguson, Sarah Osentoski: Learning Representation and Control in Continuous Markov Decision Processes. AAAI 2006
47EEMauro Maggioni, Sridhar Mahadevan: Fast direct policy evaluation using multiscale analysis of Markov diffusion processes. ICML 2006: 601-608
46EEKimberly Ferguson, Ivon Arroyo, Sridhar Mahadevan, Beverly Park Woolf, Andrew G. Barto: Improving Intelligent Tutoring Systems: Using Expectation Maximization to Learn Student Skill Levels. Intelligent Tutoring Systems 2006: 453-462
45EEJeffrey Johns, Sridhar Mahadevan, Beverly Park Woolf: Estimating Student Proficiency Using an Item Response Theory Model. Intelligent Tutoring Systems 2006: 473-480
44EEMohammad Ghavamzadeh, Sridhar Mahadevan, Rajbala Makar: Hierarchical multi-agent reinforcement learning. Autonomous Agents and Multi-Agent Systems 13(2): 197-229 (2006)
2005
43 Sridhar Mahadevan: Samuel Meets Amarel: Automating Value Function Approximation Using Global State Space Analysis. AAAI 2005: 1000-1005
42 Jeffrey Johns, Sridhar Mahadevan: A Variational Learning Algorithm for the Abstract Hidden Markov Model. AAAI 2005: 9-14
41EESridhar Mahadevan: Proto-value functions: developmental reinforcement learning. ICML 2005: 553-560
40EEKhashayar Rohanimanesh, Sridhar Mahadevan: Coarticulation: an approach for generating concurrent plans in Markov decision processes. ICML 2005: 720-727
39EESridhar Mahadevan, Mauro Maggioni: Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions. NIPS 2005
38EESridhar Mahadevan: Representation Policy Iteration. UAI 2005: 372-379
2004
37EEMohammad Ghavamzadeh, Sridhar Mahadevan: Learning to Communicate and Act Using Hierarchical Reinforcement Learning. AAMAS 2004: 1114-1121
36 Suchi Saria, Sridhar Mahadevan: Probabilistic Plan Recognition in Multiagent Systems. ICAPS 2004: 287-296
35EEKhashayar Rohanimanesh, Robert Platt Jr., Sridhar Mahadevan, Roderic A. Grupen: Coarticulation in Markov Decision Processes. NIPS 2004
2003
34 Mohammad Ghavamzadeh, Sridhar Mahadevan: Hierarchical Policy Gradient Algorithms. ICML 2003: 226-233
33EEAndrew G. Barto, Sridhar Mahadevan: Recent Advances in Hierarchical Reinforcement Learning. Discrete Event Dynamic Systems 13(1-2): 41-77 (2003)
32EEAndrew G. Barto, Sridhar Mahadevan: Recent Advances in Hierarchical Reinforcement Learning. Discrete Event Dynamic Systems 13(4): 341-379 (2003)
2002
31EEMohammad Ghavamzadeh, Sridhar Mahadevan: A multiagent reinforcement learning algorithm by dynamically merging markov decision processes. AAMAS 2002: 845-846
30 Mohammad Ghavamzadeh, Sridhar Mahadevan: Hierarchically Optimal Average Reward Reinforcement Learning. ICML 2002: 195-202
29 Georgios Theocharous, Sridhar Mahadevan: Approximate Planning with Hierarchical Partially Observable Markov Decision Process Models for Robot Navigation. ICRA 2002: 1347-1352
28EEKhashayar Rohanimanesh, Sridhar Mahadevan: Learning to Take Concurrent Actions. NIPS 2002: 1619-1626
27EESridhar Mahadevan: Spatiotemporal Abstraction of Stochastic Sequential Processes. SARA 2002: 33-50
2001
26EERajbala Makar, Sridhar Mahadevan, Mohammad Ghavamzadeh: Hierarchical multi-agent reinforcement learning. Agents 2001: 246-253
25EESilviu Minut, Sridhar Mahadevan: A reinforcement learning model of selective visual attention. Agents 2001: 457-464
24 Mohammad Ghavamzadeh, Sridhar Mahadevan: Continuous-Time Hierarchical Reinforcement Learning. ICML 2001: 186-193
23 Georgios Theocharous, Khashayar Rohanimanesh, Sridhar Mahadevan: Learning Hierarchical Partially Observable Markov Decision Process Models for Robot Navigation. ICRA 2001: 511-516
22EEKhashayar Rohanimanesh, Sridhar Mahadevan: Decision-Theoretic Planning with Concurrent Temporally Extended Actions. UAI 2001: 472-479
2000
21EESilviu Minut, Sridhar Mahadevan, John M. Henderson, Fred C. Dyer: Face Recognition Using Foveal Vision. Biologically Motivated Computer Vision 2000: 424-433
20 Natalia Hernandez-Gardiol, Sridhar Mahadevan: Hierarchical Memory-Based Reinforcement Learning. NIPS 2000: 1047-1053
1999
19 Gang Wang, Sridhar Mahadevan: Hierarchical Optimization of Policy-Coupled Semi-Markov Decision Processes. ICML 1999: 464-473
1998
18 Sridhar Mahadevan, Georgios Theocharous: Optimizing Production Manufacturing Using Reinforcement Learning. FLAIRS Conference 1998: 372-377
17 Sridhar Mahadevan, Georgios Theocharous, Nikfar Khaleeli: Rapid Concept Learning for Mobile Robots. Auton. Robots 5(3-4): 239-251 (1998)
16 Sridhar Mahadevan, Georgios Theocharous, Nikfar Khaleeli: Rapid Concept Learning for Mobile Robots. Machine Learning 31(1-3): 7-27 (1998)
1996
15 Sridhar Mahadevan: An Average-Reward Reinforcement Learning Algorithm for Computing Bias-Optimal Policies. AAAI/IAAI, Vol. 1 1996: 875-880
14 Sridhar Mahadevan: Sensitive Discount Optimality: Unifying Discounted and Average Reward Reinforcement Learning. ICML 1996: 328-336
13 Sridhar Mahadevan, Leslie Pack Kaelbling: The National Science Foundation Workshop on Reinforcement Learning. AI Magazine 17(4): 89-93 (1996)
12 Sridhar Mahadevan: Average Reward Reinforcement Learning: Foundations, Algorithms, and Empirical Results. Machine Learning 22(1-3): 159-195 (1996)
1994
11 Sridhar Mahadevan: To Discount or Not to Discount in Reinforcement Learning: A Case Study Comparing R Learning and Q Learning. ICML 1994: 164-172
10 Sridhar Mahadevan, Prasad Tadepalli: Quantifying Prior Determination Knowledge Using the PAC Learning Model. Machine Learning 17(1): 69-105 (1994)
1993
9 Sridhar Mahadevan, Tom M. Mitchell, Jack Mostow, Louis I. Steinberg, Prasad Tadepalli: An Apprentice-Based Approach to Knowledge Acquisition. Artif. Intell. 64(1): 1-52 (1993)
1992
8 Sridhar Mahadevan: Enhancing Transfer in Reinforcement Learning by Building Stochastic Models of Robot Actions. ML 1992: 290-299
7 Sridhar Mahadevan, Jonathan Connell: Automatic Programming of Behavior-Based Robots Using Reinforcement Learning. Artif. Intell. 55(2): 311-365 (1992)
1991
6 Sridhar Mahadevan, Jonathan Connell: Automatic Programming of Behavior-Based Robots Using Reinforcement Learning. AAAI 1991: 768-773
5 Sridhar Mahadevan, Jonathan Connell: Scaling Reinforcement Learning to Robotics by Exploiting the Subsumption Architecture. ML 1991: 328-332
1989
4 Sridhar Mahadevan: Using Determinations in EBL: A Solution to the incomplete Theory Problem. ML 1989: 320-325
1988
3 Sridhar Mahadevan, Prasad Tadepalli: On the Tractability of Learning from Incomplete Theories. ML 1988: 235-241
1985
2 Tom M. Mitchell, Sridhar Mahadevan, Louis I. Steinberg: LEAP: A Learning Apprentice for VLSl Design. IJCAI 1985: 573-580
1 Sridhar Mahadevan: Verification-based Learning: A Generalized Strategy for Inferring Problem-Reduction Methods. IJCAI 1985: 616-623

Coauthor Index

1Ivon Arroyo [46] [53]
2Andrew G. Barto [32] [33] [46] [53]
3Jonathan H. Connell (Jonathan Connell) [5] [6] [7]
4Toby Dragon [53]
5Fred C. Dyer [21]
6Kimberly Ferguson [46] [48] [52] [53] [61]
7Don Fisher [53]
8Mohammad Ghavamzadeh [24] [26] [30] [31] [34] [37] [44]
9Roderic A. Grupen [35]
10John M. Henderson [21]
11Natalia Hernandez-Gardiol [20]
12Jeffrey Johns [42] [45] [51] [52] [53] [54] [60]
13Leslie Pack Kaelbling [13]
14Nikfar Khaleeli [16] [17]
15Mauro Maggioni [39] [47] [48]
16Rajbala Makar [26] [44]
17Hasmik Meheranian [53]
18Silviu Minut [21] [25]
19Tom M. Mitchell [2] [9]
20Jack Mostow [9]
21Sarah Osentoski [48] [49] [52]
22Marek Petrik [60]
23Robert Platt Jr. [35]
24Khashayar Rohanimanesh [22] [23] [28] [35] [40]
25Suchi Saria [36]
26Louis I. Steinberg [2] [9]
27Prasad Tadepalli [3] [9] [10]
28Georgios Theocharous [16] [17] [18] [23] [29]
29Chang Wang [52] [54] [55] [58] [59]
30Gang Wang [19]
31Beverly Park Woolf [45] [46] [53] [61]

Colors in the list of coauthors

Copyright © Tue Nov 3 08:52:44 2009 by Michael Ley (ley@uni-trier.de)