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Prasad Tadepalli Vis

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*2009
51EEScott Proper, Prasad Tadepalli: Solving multiagent assignment Markov decision processes. AAMAS (1) 2009: 681-688
2008
50 Hendrik Blockeel, Jan Ramon, Jude W. Shavlik, Prasad Tadepalli: Inductive Logic Programming, 17th International Conference, ILP 2007, Corvallis, OR, USA, June 19-21, 2007, Revised Selected Papers Springer 2008
49EENeville Mehta, Soumya Ray, Prasad Tadepalli, Thomas G. Dietterich: Automatic discovery and transfer of MAXQ hierarchies. ICML 2008: 648-655
48EESriraam Natarajan, Hung H. Bui, Prasad Tadepalli, Kristian Kersting, Weng-Keen Wong: Logical Hierarchical Hidden Markov Models for Modeling User Activities. ILP 2008: 192-209
47EESriraam Natarajan, Prasad Tadepalli, Thomas G. Dietterich, Alan Fern: Learning first-order probabilistic models with combining rules. Ann. Math. Artif. Intell. 54(1-3): 223-256 (2008)
46EEHendrik Blockeel, Jude W. Shavlik, Prasad Tadepalli: Guest editors' introduction: special issue on inductive logic programming (ILP-2007). Machine Learning 73(1): 1-2 (2008)
45EEThomas G. Dietterich, Pedro Domingos, Lise Getoor, Stephen Muggleton, Prasad Tadepalli: Structured machine learning: the next ten years. Machine Learning 73(1): 3-23 (2008)
44EENeville Mehta, Sriraam Natarajan, Prasad Tadepalli, Alan Fern: Transfer in variable-reward hierarchical reinforcement learning. Machine Learning 73(3): 289-312 (2008)
2007
43EEAaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepalli: Multi-task reinforcement learning: a hierarchical Bayesian approach. ICML 2007: 1015-1022
42EECharles Parker, Alan Fern, Prasad Tadepalli: Learning for efficient retrieval of structured data with noisy queries. ICML 2007: 729-736
41EEAlan Fern, Sriraam Natarajan, Kshitij Judah, Prasad Tadepalli: A Decision-Theoretic Model of Assistance. IJCAI 2007: 1879-1884
40EESriraam Natarajan, Prasad Tadepalli, Alan Fern: A Relational Hierarchical Model for Decision-Theoretic Assistance. ILP 2007: 175-190
39 Sriraam Natarajan, Kshitij Judah, Prasad Tadepalli, Alan Fern: A Decision-Theoretic Model of Assistance - Evaluation, Extensions and Open Problems. Interaction Challenges for Intelligent Assistants 2007: 90-97
38EESriraam Natarajan, Prasad Tadepalli, Alan Fern: Exploiting prior knowledge in Intelligent Assistants - Combining relational models with hierarchies. Probabilistic, Logical and Relational Learning - A Further Synthesis 2007
2006
37 Charles Parker, Alan Fern, Prasad Tadepalli: Gradient Boosting for Sequence Alignment. AAAI 2006
36EEScott Proper, Prasad Tadepalli: Scaling Model-Based Average-Reward Reinforcement Learning for Product Delivery. ECML 2006: 735-742
2005
35EESriraam Natarajan, Prasad Tadepalli: Dynamic preferences in multi-criteria reinforcement learning. ICML 2005: 601-608
34EESriraam Natarajan, Prasad Tadepalli, Eric Altendorf, Thomas G. Dietterich, Alan Fern, Angelo C. Restificar: Learning first-order probabilistic models with combining rules. ICML 2005: 609-616
2002
33 Sandeep Seri, Prasad Tadepalli: Model-based Hierarchical Average-reward Reinforcement Learning. ICML 2002: 562-569
32 Michael Chisholm, Prasad Tadepalli: Learning Decision Rules by Randomized Iterative Local Search. ICML 2002: 75-82
2001
31 Thomas R. Amoth, Paul Cull, Prasad Tadepalli: On Exact Learning of Unordered Tree Patterns. Machine Learning 44(3): 211-243 (2001)
1999
30EEThomas R. Amoth, Paul Cull, Prasad Tadepalli: Exact Learning of Unordered Tree Patterns from Queries. COLT 1999: 323-332
29 Chandra Reddy, Prasad Tadepalli: Learning Horn Definitions: Theory and an Application to Planning. New Generation Comput. 17(1): 77-98 (1999)
1998
28EEThomas R. Amoth, Paul Cull, Prasad Tadepalli: Exact Learning of Tree Patterns from Queries and Counterexamples. COLT 1998: 175-186
27 Chandra Reddy, Prasad Tadepalli: Learning First-Order Acyclic Horn Programs from Entailment. ICML 1998: 472-480
26 Chandra Reddy, Prasad Tadepalli: Learning First-Order Acyclic Horn Programs from Entailment. ILP 1998: 23-37
25EEPrasad Tadepalli, DoKyeong Ok: Model-Based Average Reward Reinforcement Learning. Artif. Intell. 100(1-2): 177-223 (1998)
24 Prasad Tadepalli, Stuart J. Russell: Learning from Examples and Membership Queries with Structured Determinations. Machine Learning 32(3): 245-295 (1998)
1997
23 Ray Liere, Prasad Tadepalli: Active Learning with Committees for Text Categorization. AAAI/IAAI 1997: 591-596
22 Ray Liere, Prasad Tadepalli: Active Learning with Committees. AAAI/IAAI 1997: 838
21 Chandra Reddy, Prasad Tadepalli: Learning Goal-Decomposition Rules Using Exercises. AAAI/IAAI 1997: 843
20 Chandra Reddy, Prasad Tadepalli: Learning Goal-Decomposition Rules using Exercises. ICML 1997: 278-286
19 Prasad Tadepalli, Thomas G. Dietterich: Hierarchical Explanation-Based Reinforcement Learning. ICML 1997: 358-366
18 Chandra Reddy, Prasad Tadepalli: Learning Horn Definitions with Equivalence and Membership Queries. ILP 1997: 243-255
1996
17 DoKyeong Ok, Prasad Tadepalli: Auto-Exploratory Average Reward Reinforcement Learning. AAAI/IAAI, Vol. 1 1996: 881-887
16 Chandra Reddy, Prasad Tadepalli, Silvana Roncagliolo: Theory-guided Empirical Speedup Learning of Goal Decomposition Rules. ICML 1996: 409-417
15 Prasad Tadepalli, DoKyeong Ok: Scaling Up Average Reward Reinforcement Learning by Approximating the Domain Models and the Value Function. ICML 1996: 471-479
14EEPrasad Tadepalli, Balas K. Natarajan: A Formal Framework for Speedup Learning from Problems and Solutions CoRR cs.AI/9605105: (1996)
13 Prasad Tadepalli, Balas K. Natarajan: A Formal Framework for Speedup Learning from Problems and Solutions. J. Artif. Intell. Res. (JAIR) 4: 445-475 (1996)
1994
12 Sridhar Mahadevan, Prasad Tadepalli: Quantifying Prior Determination Knowledge Using the PAC Learning Model. Machine Learning 17(1): 69-105 (1994)
1993
11 Prasad Tadepalli: Learning from Queries and Examples with Tree-structured Bias. ICML 1993: 322-329
10 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
9 Prasad Tadepalli: A Theory of Unsupervised Speedup Learning. AAAI 1992: 229-234
1991
8 Prasad Tadepalli: A Formalization of Explanation-Based Macro-operator Learning. IJCAI 1991: 616-622
7 Prasad Tadepalli: Learning with Incrutable Theories. ML 1991: 544-548
1990
6 Sholom M. Weiss, Robert S. Galen, Prasad Tadepalli: Maximizing the Predictive Value of Production Rules. Artif. Intell. 45(1-2): 47-71 (1990)
1989
5 Prasad Tadepalli: Lazy ExplanationBased Learning: A Solution to the Intractable Theory Problem. IJCAI 1989: 694-700
4 Prasad Tadepalli: Planning Approximate Plans for Use in the Real World. ML 1989: 224-228
1988
3 Sridhar Mahadevan, Prasad Tadepalli: On the Tractability of Learning from Incomplete Theories. ML 1988: 235-241
2 Balas K. Natarajan, Prasad Tadepalli: Two New Frameworks for Learning. ML 1988: 402-415
1987
1 Sholom M. Weiss, Robert S. Galen, Prasad Tadepalli: Optimizing the Predictive Value of Diagnostic Decision Rules. AAAI 1987: 521-527

Coauthor Index

1Eric Altendorf [34]
2Thomas R. Amoth [28] [30] [31]
3Hendrik Blockeel [46] [50]
4Hung H. Bui [48]
5Michael Chisholm [32]
6Paul Cull [28] [30] [31]
7Thomas G. Dietterich [19] [34] [45] [47] [49]
8Pedro Domingos [45]
9Alan Fern [34] [37] [38] [39] [40] [41] [42] [43] [44] [47]
10Robert S. Galen [1] [6]
11Lise Getoor [45]
12Kshitij Judah [39] [41]
13Kristian Kersting [48]
14Ray Liere [22] [23]
15Sridhar Mahadevan [3] [10] [12]
16Neville Mehta [44] [49]
17Tom M. Mitchell [10]
18Jack Mostow [10]
19Stephen Muggleton [45]
20Balas K. Natarajan (B. K. Natarajan) [2] [13] [14]
21Sriraam Natarajan [34] [35] [38] [39] [40] [41] [44] [47] [48]
22DoKyeong Ok [15] [17] [25]
23Charles Parker [37] [42]
24Scott Proper [36] [51]
25Jan Ramon [50]
26Soumya Ray [43] [49]
27Chandra Reddy [16] [18] [20] [21] [26] [27] [29]
28Angelo C. Restificar [34]
29Silvana Roncagliolo [16]
30Stuart J. Russell [24]
31Sandeep Seri [33]
32Jude W. Shavlik [46] [50]
33Louis I. Steinberg [10]
34Sholom M. Weiss [1] [6]
35Aaron Wilson [43]
36Weng-Keen Wong [48]

Colors in the list of coauthors

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