Prasad Tadepalli - researchr alias

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2011

2010

Learning Algorithms for Link Prediction Based on Chance ConstraintsJanardhan Rao Doppa, Jun Yu, Prasad Tadepalli, Lise Getoor. pkdd 2010: 344-360 [doi]

Multi-Agent Inverse Reinforcement LearningSriraam Natarajan, Gautam Kunapuli, Kshitij Judah, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik. icmla 2010: 395-400 [doi]

Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed ModelsSriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik. pkdd 2010: 434-450 [doi]

Bayesian role discovery for multi-agent reinforcement learningAaron Wilson, Alan Fern, Prasad Tadepalli. atal 2010: 1587-1588 [doi]

Incorporating Domain Models into Bayesian Optimization for RLAaron Wilson, Alan Fern, Prasad Tadepalli. pkdd 2010: 467-482 [doi]

Bayesian Policy Search for Multi-Agent Role DiscoveryAaron Wilson, Alan Fern, Prasad Tadepalli. AAAI 2010: [doi]

2009

Lower Bounding Klondike Solitaire with Monte-Carlo PlanningRonald Bjarnason, Alan Fern, Prasad Tadepalli. aips 2009:

Simulation-based Optimization of Resource Placement and Emergency ResponseRonald Bjarnason, Prasad Tadepalli, Alan Fern, Carl Niedner. iaai 2009: [doi]

Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining RuleSriraam Natarajan, Prasad Tadepalli, Gautam Kunapuli, Jude W. Shavlik. icmla 2009: 141-146 [doi]

Guest editorial: special issue on structured predictionCharles Parker, Yasemin Altun, Prasad Tadepalli. ml, 77(2-3):161-164, 2009. [doi]

Transfer Learning via Relational TemplatesScott Proper, Prasad Tadepalli. ilp 2010: 186-193 [doi]

Solving multiagent assignment Markov decision processesScott Proper, Prasad Tadepalli. atal 2009: 681-688 [doi]

Multiagent Transfer Learning via Assignment-Based DecompositionScott Proper, Prasad Tadepalli. icmla 2009: 345-350 [doi]

2008

Inductive Logic Programming, 17th International Conference, ILP 2007, Corvallis, OR, USA, June 19-21, 2007, Revised Selected PapersHendrik Blockeel, Jan Ramon, Jude W. Shavlik, Prasad Tadepalli, editors, Volume 4894 of Lecture Notes in Computer Science, Springer, 2008.

Guest editors introduction: special issue on inductive logic programming (ILP-2007)Hendrik Blockeel, Jude W. Shavlik, Prasad Tadepalli. ml, 73(1):1-2, 2008. [doi]

Structured machine learning: the next ten yearsThomas G. Dietterich, Pedro Domingos, Lise Getoor, Stephen Muggleton, Prasad Tadepalli. ml, 73(1):3-23, 2008. [doi]

Transfer in variable-reward hierarchical reinforcement learningNeville Mehta, Sriraam Natarajan, Prasad Tadepalli, Alan Fern. ml, 73(3):289-312, 2008. [doi]

Automatic discovery and transfer of MAXQ hierarchiesNeville Mehta, Soumya Ray, Prasad Tadepalli, Thomas G. Dietterich. icml 2008: 648-655 [doi]

Logical Hierarchical Hidden Markov Models for Modeling User ActivitiesSriraam Natarajan, Hung H. Bui, Prasad Tadepalli, Kristian Kersting, Weng-Keen Wong. ilp 2008: 192-209 [doi]

Learning first-order probabilistic models with combining rulesSriraam Natarajan, Prasad Tadepalli, Thomas G. Dietterich, Alan Fern. AMAI, 54(1-3):223-256, 2008. [doi]

Learning to Solve Problems from ExercisesPrasad Tadepalli. ci, 24(4):257-291, 2008. [doi]

2007

Searching Solitaire in Real TimeRonald Bjarnason, Prasad Tadepalli, Alan Fern. icga, 30(3):131-142, 2007.

A Decision-Theoretic Model of AssistanceAlan Fern, Sriraam Natarajan, Kshitij Judah, Prasad Tadepalli. IJCAI 2007: 1879-1884 [doi]

Exploiting prior knowledge in Intelligent Assistants - Combining relational models with hierarchiesSriraam Natarajan, Prasad Tadepalli, Alan Fern. dagstuhl 2008: [doi]

A Relational Hierarchical Model for Decision-Theoretic AssistanceSriraam Natarajan, Prasad Tadepalli, Alan Fern. ilp 2008: 175-190 [doi]

A Decision-Theoretic Model of Assistance - Evaluation, Extensions and Open ProblemsSriraam Natarajan, Kshitij Judah, Prasad Tadepalli, Alan Fern. icia 2007: 90-97

Learning for efficient retrieval of structured data with noisy queriesCharles Parker, Alan Fern, Prasad Tadepalli. icml 2007: 729-736 [doi]

Multi-task reinforcement learning: a hierarchical Bayesian approachAaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepalli. icml 2007: 1015-1022 [doi]

2006

Gradient Boosting for Sequence AlignmentCharles Parker, Alan Fern, Prasad Tadepalli. AAAI 2006:

Scaling Model-Based Average-Reward Reinforcement Learning for Product DeliveryScott Proper, Prasad Tadepalli. ecml 2006: 735-742 [doi]

2005

Dynamic preferences in multi-criteria reinforcement learningSriraam Natarajan, Prasad Tadepalli. icml 2005: 601-608 [doi]

Learning first-order probabilistic models with combining rulesSriraam Natarajan, Prasad Tadepalli, Eric Altendorf, Thomas G. Dietterich, Alan Fern, Angelo C. Restificar. icml 2005: 609-616 [doi]

2002

Learning Decision Rules by Randomized Iterative Local SearchMichael Chisholm, Prasad Tadepalli. icml 2002: 75-82

Model-based Hierarchical Average-reward Reinforcement LearningSandeep Seri, Prasad Tadepalli. icml 2002: 562-569

2001

On Exact Learning of Unordered Tree PatternsThomas R. Amoth, Paul Cull, Prasad Tadepalli. ml, 44(3):211-243, 2001.

1999

Exact Learning of Unordered Tree Patterns from QueriesThomas R. Amoth, Paul Cull, Prasad Tadepalli. colt 1999: 323-332 [doi]

Learning Horn Definitions: Theory and an Application to PlanningChandra Reddy, Prasad Tadepalli. ngc, 17(1):77-98, 1999.

1998

1997

1996

Auto-Exploratory Average Reward Reinforcement LearningDoKyeong Ok, Prasad Tadepalli. AAAI 1996: 881-887

Theory-guided Empirical Speedup Learning of Goal Decomposition RulesChandra Reddy, Prasad Tadepalli, Silvana Roncagliolo. icml 1996: 409-417

Scaling Up Average Reward Reinforcement Learning by Approximating the Domain Models and the Value FunctionPrasad Tadepalli, DoKyeong Ok. icml 1996: 471-479

A Formal Framework for Speedup Learning from Problems and SolutionsPrasad Tadepalli, Balas K. Natarajan. jair, 4:445-475, 1996.

1994

Quantifying Prior Determination Knowledge Using the PAC Learning ModelSridhar Mahadevan, Prasad Tadepalli. ml, 17(1):69-105, 1994.

1993

An Apprentice-Based Approach to Knowledge AcquisitionSridhar Mahadevan, Tom M. Mitchell, Jack Mostow, Louis I. Steinberg, Prasad Tadepalli. ai, 64(1):1-52, 1993.

Learning from Queries and Examples with Tree-structured BiasPrasad Tadepalli. icml 1993: 322-329

1992

A Theory of Unsupervised Speedup LearningPrasad Tadepalli. AAAI 1992: 229-234

1991

Learning with Incrutable TheoriesPrasad Tadepalli. icml 1991: 544-548

A Formalization of Explanation-Based Macro-operator LearningPrasad Tadepalli. IJCAI 1991: 616-622

1990

Maximizing the Predictive Value of Production RulesSholom M. Weiss, Robert S. Galen, Prasad Tadepalli. ai, 45(1-2):47-71, 1990.

1989

Planning Approximate Plans for Use in the Real WorldPrasad Tadepalli. icml 1989: 224-228

Lazy ExplanationBased Learning: A Solution to the Intractable Theory ProblemPrasad Tadepalli. IJCAI 1989: 694-700

1988

On the Tractability of Learning from Incomplete TheoriesSridhar Mahadevan, Prasad Tadepalli. icml 1988: 235-241

Two New Frameworks for LearningBalas K. Natarajan, Prasad Tadepalli. icml 1988: 402-415

1987

Optimizing the Predictive Value of Diagnostic Decision RulesSholom M. Weiss, Robert S. Galen, Prasad Tadepalli. AAAI 1987: 521-527