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## Search the dblp DataBase
Prasad Tadepalli:
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## Publications of Author- Ray Liere, Prasad Tadepalli
**Active Learning with Committees for Text Categorization.**[Citation Graph (0, 0)][DBLP] AAAI/IAAI, 1997, pp:591-596 [Conf] - Ray Liere, Prasad Tadepalli
**Active Learning with Committees.**[Citation Graph (0, 0)][DBLP] AAAI/IAAI, 1997, pp:838- [Conf] - DoKyeong Ok, Prasad Tadepalli
**Auto-Exploratory Average Reward Reinforcement Learning.**[Citation Graph (0, 0)][DBLP] AAAI/IAAI, Vol. 1, 1996, pp:881-887 [Conf] - Charles Parker, Alan Fern, Prasad Tadepalli
**Gradient Boosting for Sequence Alignment.**[Citation Graph (0, 0)][DBLP] AAAI, 2006, pp:- [Conf] - Chandra Reddy, Prasad Tadepalli
**Learning Goal-Decomposition Rules Using Exercises.**[Citation Graph (0, 0)][DBLP] AAAI/IAAI, 1997, pp:843- [Conf] - Prasad Tadepalli
**A Theory of Unsupervised Speedup Learning.**[Citation Graph (0, 0)][DBLP] AAAI, 1992, pp:229-234 [Conf] - Sholom M. Weiss, Robert S. Galen, Prasad Tadepalli
**Optimizing the Predictive Value of Diagnostic Decision Rules.**[Citation Graph (0, 0)][DBLP] AAAI, 1987, pp:521-527 [Conf] - Thomas R. Amoth, Paul Cull, Prasad Tadepalli
**Exact Learning of Tree Patterns from Queries and Counterexamples.**[Citation Graph (0, 0)][DBLP] COLT, 1998, pp:175-186 [Conf] - Thomas R. Amoth, Paul Cull, Prasad Tadepalli
**Exact Learning of Unordered Tree Patterns from Queries.**[Citation Graph (0, 0)][DBLP] COLT, 1999, pp:323-332 [Conf] - Scott Proper, Prasad Tadepalli
**Scaling Model-Based Average-Reward Reinforcement Learning for Product Delivery.**[Citation Graph (0, 0)][DBLP] ECML, 2006, pp:735-742 [Conf] - Michael Chisholm, Prasad Tadepalli
**Learning Decision Rules by Randomized Iterative Local Search.**[Citation Graph (0, 0)][DBLP] ICML, 2002, pp:75-82 [Conf] - Sridhar Mahadevan, Prasad Tadepalli
**On the Tractability of Learning from Incomplete Theories.**[Citation Graph (0, 0)][DBLP] ML, 1988, pp:235-241 [Conf] - Sriraam Natarajan, Prasad Tadepalli
**Dynamic preferences in multi-criteria reinforcement learning.**[Citation Graph (0, 0)][DBLP] ICML, 2005, pp:601-608 [Conf] - Balas K. Natarajan, Prasad Tadepalli
**Two New Frameworks for Learning.**[Citation Graph (0, 0)][DBLP] ML, 1988, pp:402-415 [Conf] - Sriraam Natarajan, Prasad Tadepalli, Eric Altendorf, Thomas G. Dietterich, Alan Fern, Angelo C. Restificar
**Learning first-order probabilistic models with combining rules.**[Citation Graph (0, 0)][DBLP] ICML, 2005, pp:609-616 [Conf] - Chandra Reddy, Prasad Tadepalli
**Learning Goal-Decomposition Rules using Exercises.**[Citation Graph (0, 0)][DBLP] ICML, 1997, pp:278-286 [Conf] - Chandra Reddy, Prasad Tadepalli
**Learning First-Order Acyclic Horn Programs from Entailment.**[Citation Graph (0, 0)][DBLP] ICML, 1998, pp:472-480 [Conf] - Chandra Reddy, Prasad Tadepalli, Silvana Roncagliolo
**Theory-guided Empirical Speedup Learning of Goal Decomposition Rules.**[Citation Graph (0, 0)][DBLP] ICML, 1996, pp:409-417 [Conf] - Sandeep Seri, Prasad Tadepalli
**Model-based Hierarchical Average-reward Reinforcement Learning.**[Citation Graph (0, 0)][DBLP] ICML, 2002, pp:562-569 [Conf] - Prasad Tadepalli
**Planning Approximate Plans for Use in the Real World.**[Citation Graph (0, 0)][DBLP] ML, 1989, pp:224-228 [Conf] - Prasad Tadepalli
**Learning with Incrutable Theories.**[Citation Graph (0, 0)][DBLP] ML, 1991, pp:544-548 [Conf] - Prasad Tadepalli
**Learning from Queries and Examples with Tree-structured Bias.**[Citation Graph (0, 0)][DBLP] ICML, 1993, pp:322-329 [Conf] - Prasad Tadepalli, Thomas G. Dietterich
**Hierarchical Explanation-Based Reinforcement Learning.**[Citation Graph (0, 0)][DBLP] ICML, 1997, pp:358-366 [Conf] - Prasad Tadepalli, DoKyeong Ok
**Scaling Up Average Reward Reinforcement Learning by Approximating the Domain Models and the Value Function.**[Citation Graph (0, 0)][DBLP] ICML, 1996, pp:471-479 [Conf] - Prasad Tadepalli
**Lazy ExplanationBased Learning: A Solution to the Intractable Theory Problem.**[Citation Graph (0, 0)][DBLP] IJCAI, 1989, pp:694-700 [Conf] - Prasad Tadepalli
**A Formalization of Explanation-Based Macro-operator Learning.**[Citation Graph (0, 0)][DBLP] IJCAI, 1991, pp:616-622 [Conf] - Alan Fern, Sriraam Natarajan, Kshitij Judah, Prasad Tadepalli
**A Decision-Theoretic Model of Assistance.**[Citation Graph (0, 0)][DBLP] IJCAI, 2007, pp:1879-1884 [Conf] - Chandra Reddy, Prasad Tadepalli
**Learning Horn Definitions with Equivalence and Membership Queries.**[Citation Graph (0, 0)][DBLP] ILP, 1997, pp:243-255 [Conf] - Chandra Reddy, Prasad Tadepalli
**Learning First-Order Acyclic Horn Programs from Entailment.**[Citation Graph (0, 0)][DBLP] ILP, 1998, pp:23-37 [Conf] - Sridhar Mahadevan, Tom M. Mitchell, Jack Mostow, Louis I. Steinberg, Prasad Tadepalli
**An Apprentice-Based Approach to Knowledge Acquisition.**[Citation Graph (0, 0)][DBLP] Artif. Intell., 1993, v:64, n:1, pp:1-52 [Journal] - Prasad Tadepalli, DoKyeong Ok
**Model-Based Average Reward Reinforcement Learning.**[Citation Graph (0, 0)][DBLP] Artif. Intell., 1998, v:100, n:1-2, pp:177-223 [Journal] - Sholom M. Weiss, Robert S. Galen, Prasad Tadepalli
**Maximizing the Predictive Value of Production Rules.**[Citation Graph (0, 0)][DBLP] Artif. Intell., 1990, v:45, n:1-2, pp:47-71 [Journal] - Prasad Tadepalli, Balas K. Natarajan
**A Formal Framework for Speedup Learning from Problems and Solutions**[Citation Graph (0, 0)][DBLP] CoRR, 1996, v:0, n:, pp:- [Journal] - Prasad Tadepalli, Balas K. Natarajan
**A Formal Framework for Speedup Learning from Problems and Solutions.**[Citation Graph (0, 0)][DBLP] J. Artif. Intell. Res. (JAIR), 1996, v:4, n:, pp:445-475 [Journal] - Thomas R. Amoth, Paul Cull, Prasad Tadepalli
**On Exact Learning of Unordered Tree Patterns.**[Citation Graph (0, 0)][DBLP] Machine Learning, 2001, v:44, n:3, pp:211-243 [Journal] - Sridhar Mahadevan, Prasad Tadepalli
**Quantifying Prior Determination Knowledge Using the PAC Learning Model.**[Citation Graph (0, 0)][DBLP] Machine Learning, 1994, v:17, n:1, pp:69-105 [Journal] - Prasad Tadepalli, Stuart J. Russell
**Learning from Examples and Membership Queries with Structured Determinations.**[Citation Graph (0, 0)][DBLP] Machine Learning, 1998, v:32, n:3, pp:245-295 [Journal] - Chandra Reddy, Prasad Tadepalli
**Learning Horn Definitions: Theory and an Application to Planning.**[Citation Graph (0, 0)][DBLP] New Generation Comput., 1999, v:17, n:1, pp:77-98 [Journal] - Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepalli
**Multi-task reinforcement learning: a hierarchical Bayesian approach.**[Citation Graph (0, 0)][DBLP] ICML, 2007, pp:1015-1022 [Conf] - Charles Parker, Alan Fern, Prasad Tadepalli
**Learning for efficient retrieval of structured data with noisy queries.**[Citation Graph (0, 0)][DBLP] ICML, 2007, pp:729-736 [Conf] - Sriraam Natarajan, Kshitij Judah, Prasad Tadepalli, Alan Fern
**A Decision-Theoretic Model of Assistance - Evaluation, Extensions and Open Problems.**[Citation Graph (0, 0)][DBLP] Interaction Challenges for Intelligent Assistants, 2007, pp:90-97 [Conf] **Bayesian Policy Search for Multi-Agent Role Discovery.**[Citation Graph (, )][DBLP]**Lower Bounding Klondike Solitaire with Monte-Carlo Planning.**[Citation Graph (, )][DBLP]**Solving multiagent assignment Markov decision processes.**[Citation Graph (, )][DBLP]**Bayesian role discovery for multi-agent reinforcement learning.**[Citation Graph (, )][DBLP]**Exploiting prior knowledge in Intelligent Assistants - Combining relational models with hierarchies.**[Citation Graph (, )][DBLP]**Automatic discovery and transfer of MAXQ hierarchies.**[Citation Graph (, )][DBLP]**Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule.**[Citation Graph (, )][DBLP]**Multiagent Transfer Learning via Assignment-Based Decomposition.**[Citation Graph (, )][DBLP]**A Relational Hierarchical Model for Decision-Theoretic Assistance.**[Citation Graph (, )][DBLP]**Logical Hierarchical Hidden Markov Models for Modeling User Activities.**[Citation Graph (, )][DBLP]**Transfer Learning via Relational Templates.**[Citation Graph (, )][DBLP]**Incorporating Domain Models into Bayesian Optimization for RL.**[Citation Graph (, )][DBLP]**Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models.**[Citation Graph (, )][DBLP]**Learning Algorithms for Link Prediction Based on Chance Constraints.**[Citation Graph (, )][DBLP]**Learning first-order probabilistic models with combining rules.**[Citation Graph (, )][DBLP]**Learning to Solve Problems from Exercises.**[Citation Graph (, )][DBLP]
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