Prasad Tadepalli

184 papers A* 54A 3B 10C 9Misc 1Journal 64Unranked 39

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Local-to-Global Logical Explanations for Deep Vision Models. CoRR Bhavan K. Vasu, Giuseppe Raffa, Prasad Tadepalli
2025	A	`conf`	Combining Planning and Reinforcement Learning for Solving Relational Multiagent Domains. AAMAS Nikhilesh Prabhakar, Ranveer Singh, Harsha Kokel, Sriraam Natarajan, Prasad Tadepalli
2025	J	`jnl`	Combining Planning and Reinforcement Learning for Solving Relational Multiagent Domains. CoRR Nikhilesh Prabhakar, Ranveer Singh, Harsha Kokel, Sriraam Natarajan, Prasad Tadepalli
2025	J	`jnl`	Defenses Against Adversarial Attacks on Object Detection: Methods and Future Directions. Inf. Anant Thunuguntla, Prasad Tadepalli, Giuseppe Raffa
2025	J	`jnl`	GammaZero: Learning To Guide POMDP Belief Space Search With Graph Representations. CoRR Rajesh Mangannavar, Prasad Tadepalli
2025	J	`jnl`	Generating Part-Based Global Explanations Via Correspondence. CoRR Kunal Rathore, Prasad Tadepalli
2025	A*	`conf`	Self-attention-based Diffusion Model for Time-series Imputation in Partial Blackout Scenarios. AAAI Mohammad Rafid Ul Islam, Prasad Tadepalli, Alan Fern
2025	J	`jnl`	Self-attention-based Diffusion Model for Time-series Imputation in Partial Blackout Scenarios. CoRR Mohammad Rafid Ul Islam, Prasad Tadepalli, Alan Fern
2024	A*	`conf`	Adversarial Attacks on Combinatorial Multi-Armed Bandits. ICML Rishab Balasubramanian, Jiawei Li, Prasad Tadepalli, Huazheng Wang, Qingyun Wu, Haoyu Zhao
2024	—	`conf`	Chess Rating Estimation from Moves and Clock Times Using a CNN-LSTM. CG Michael Omori, Prasad Tadepalli
2024	J	`jnl`	Chess Rating Estimation from Moves and Clock Times Using a CNN-LSTM. CoRR Michael Omori, Prasad Tadepalli
2024	J	`jnl`	Explainable models via compression of tree ensembles. Mach. Learn. Siwen Yan, Sriraam Natarajan, Saket Joshi, Roni Khardon, Prasad Tadepalli
2024	J	`jnl`	GABAR: Graph Attention-Based Action Ranking for Relational Policy Learning. CoRR Rajesh Mangannavar, Stefan Lee, Alan Fern, Prasad Tadepalli
2024	J	`jnl`	Hierarchical Object-Oriented POMDP Planning for Object Rearrangement. CoRR Rajesh Mangannavar, Alan Fern, Prasad Tadepalli
2024	—	`conf`	Language-Informed Beam Search Decoding for Multilingual Machine Translation. ACL (Findings) Yilin Yang, Stefan Lee, Prasad Tadepalli
2024	J	`jnl`	Language-Informed Beam Search Decoding for Multilingual Machine Translation. CoRR Yilin Yang, Stefan Lee, Prasad Tadepalli
2023	J	`jnl`	Adversarial Attacks on Combinatorial Multi-Armed Bandits. CoRR Rishab Balasubramanian, Jiawei Li, Prasad Tadepalli, Huazheng Wang, Qingyun Wu, Haoyu Zhao
2023	A*	`conf`	Global Explanations for Image Classifiers (Student Abstract). AAAI Bhavan K. Vasu, Prasad Tadepalli
2023	J	`jnl`	RePReL: a unified framework for integrating relational planning and reinforcement learning for effective abstraction in discrete and continuous domains. Neural Comput. Appl. Harsha Kokel, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli
2022	J	`jnl`	Explainable Models via Compression of Tree Ensembles. CoRR Siwen Yan, Sriraam Natarajan, Saket Joshi, Roni Khardon, Prasad Tadepalli
2022	J	`jnl`	Formalizing the Problem of Side Effect Regularization. CoRR Alexander Matt Turner, Aseem Saxena, Prasad Tadepalli
2022	C	`conf`	Hybrid Deep RePReL: Integrating Relational Planning and Reinforcement Learning for Information Fusion. FUSION Harsha Kokel, Nikhilesh Prabhakar, Balaraman Ravindran, Erik Blasch, Prasad Tadepalli, Sriraam Natarajan
2022	A*	`conf`	Parametrically Retargetable Decision-Makers Tend To Seek Power. NeurIPS Alexander Matt Turner, Prasad Tadepalli
2022	J	`jnl`	Parametrically Retargetable Decision-Makers Tend To Seek Power. CoRR Alexander Matt Turner, Prasad Tadepalli
2021	A*	`conf`	DeepAveragers: Offline Reinforcement Learning By Solving Derived Non-Parametric MDPs. ICLR Aayam Kumar Shrestha, Stefan Lee, Prasad Tadepalli, Alan Fern
2021	J	`jnl`	Dynamic probabilistic logic models for effective abstractions in RL. CoRR Harsha Kokel, Arjun Manoharan, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli
2021	J	`jnl`	From Heatmaps to Structural Explanations of Image Classifiers. CoRR Fuxin Li, Zhongang Qi, Saeed Khorram, Vivswan Shitole, Prasad Tadepalli, Minsuk Kahng, Alan Fern
2021	—	`conf`	Improving Multilingual Translation by Representation and Gradient Regularization. EMNLP (1) Yilin Yang, Akiko Eriguchi, Alexandre Muzio, Prasad Tadepalli, Stefan Lee, Hany Hassan
2021	J	`jnl`	Improving Multilingual Translation by Representation and Gradient Regularization. CoRR Yilin Yang, Akiko Eriguchi, Alexandre Muzio, Prasad Tadepalli, Stefan Lee, Hany Hassan
2021	A*	`conf`	One Explanation is Not Enough: Structured Attention Graphs for Image Classification. NeurIPS Vivswan Shitole, Fuxin Li, Minsuk Kahng, Prasad Tadepalli, Alan Fern
2021	A*	`conf`	Optimal Policies Tend To Seek Power. NeurIPS Alexander Matt Turner, Logan Smith, Rohin Shah, Andrew Critch, Prasad Tadepalli
2021	A*	`conf`	PAC Learning of Causal Trees with Latent Variables. AAAI Prasad Tadepalli, Stuart J. Russell
2021	A*	`conf`	RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction. ICAPS Harsha Kokel, Arjun Manoharan, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli
2020	A*	`conf`	Avoiding Side Effects in Complex Environments. NeurIPS Alexander Matt Turner, Neale Ratzlaff, Prasad Tadepalli
2020	J	`jnl`	Avoiding Side Effects in Complex Environments. CoRR Alexander Matt Turner, Neale Ratzlaff, Prasad Tadepalli
2020	C	`conf`	Conservative Agency via Attainable Utility Preservation. AIES Alexander Matt Turner, Dylan Hadfield-Menell, Prasad Tadepalli
2020	J	`jnl`	DeepAveragers: Offline Reinforcement Learning by Solving Derived Non-Parametric MDPs. CoRR Aayam Shrestha, Stefan Lee, Prasad Tadepalli, Alan Fern
2020	—	`conf`	On the Sub-Layer Functionalities of Transformer Decoder. EMNLP (Findings) Yilin Yang, Longyue Wang, Shuming Shi, Prasad Tadepalli, Stefan Lee, Zhaopeng Tu
2020	J	`jnl`	On the Sub-Layer Functionalities of Transformer Decoder. CoRR Yilin Yang, Longyue Wang, Shuming Shi, Prasad Tadepalli, Stefan Lee, Zhaopeng Tu
2020	A*	`conf`	Relation Extraction with Explanation. ACL Hamed Shahbazi, Xiaoli Z. Fern, Reza Ghaeini, Prasad Tadepalli
2020	J	`jnl`	Relation Extraction with Explanation. CoRR Hamed Shahbazi, Xiaoli Z. Fern, Reza Ghaeini, Prasad Tadepalli
2020	J	`jnl`	Structured Attention Graphs for Understanding Deep Image Classifications. CoRR Vivswan Shitole, Fuxin Li, Minsuk Kahng, Prasad Tadepalli, Alan Fern
2020	A*	`conf`	The Choice Function Framework for Online Policy Improvement. AAAI Murugeswari Issakkimuthu, Alan Fern, Prasad Tadepalli
2019	J	`jnl`	Conservative Agency via Attainable Utility Preservation. CoRR Alexander Matt Turner, Dylan Hadfield-Menell, Prasad Tadepalli
2019	—	`conf`	Conservative Agency. AISafety@IJCAI Alexander Matt Turner, Dylan Hadfield-Menell, Prasad Tadepalli
2019	—	`conf`	Description-Based Zero-shot Fine-Grained Entity Typing. NAACL-HLT (1) Rasha Obeidat, Xiaoli Z. Fern, Hamed Shahbazi, Prasad Tadepalli
2019	J	`jnl`	Entity-aware ELMo: Learning Contextual Entity Representation for Entity Disambiguation. CoRR Hamed Shahbazi, Xiaoli Z. Fern, Reza Ghaeini, Rasha Obeidat, Prasad Tadepalli
2019	—	`conf`	Interactive Naming for Explaining Deep Neural Networks: A Formative Study. IUI Workshops Mandana Hamidi-Haines, Zhongang Qi, Alan Fern, Fuxin Li, Prasad Tadepalli
2019	Misc	`conf`	Optimizing Earth Moving Operations Via Reinforcement Learning. WSC Vivswan Shitole, Joseph Louis, Prasad Tadepalli
2019	J	`jnl`	Reports of the AAAI 2019 Spring Symposium Series. AI Mag. Ioana Baldini, Clark W. Barrett, Antonio Chella, Carlos Cinelli, David Gamez, Leilani H. Gilpin, Knut Hinkelmann, Dylan Holmes, Takashi Kido, Murat Kocaoglu, William F. Lawless, Alessio Lomuscio, Jamie C. Macbeth, Andreas Martin, Ranjeev Mittu, Evan Patterson, Donald Sofge, Prasad Tadepalli, Keiki Takadama, Shomir Wilson
2019	—	`conf`	Saliency Learning: Teaching the Model Where to Pay Attention. NAACL-HLT (1) Reza Ghaeini, Xiaoli Z. Fern, Hamed Shahbazi, Prasad Tadepalli
2019	J	`jnl`	Saliency Learning: Teaching the Model Where to Pay Attention. CoRR Reza Ghaeini, Xiaoli Z. Fern, Hamed Shahbazi, Prasad Tadepalli
2019	J	`jnl`	The Choice Function Framework for Online Policy Improvement. CoRR Murugeswari Issakkimuthu, Alan Fern, Prasad Tadepalli
2018	J	`jnl`	Attentional Multi-Reading Sarcasm Detection. CoRR Reza Ghaeini, Xiaoli Z. Fern, Prasad Tadepalli
2018	B	`conf`	Dependent Gated Reading for Cloze-Style Question Answering. COLING Reza Ghaeini, Xiaoli Z. Fern, Hamed Shahbazi, Prasad Tadepalli
2018	J	`jnl`	Dependent Gated Reading for Cloze-Style Question Answering. CoRR Reza Ghaeini, Xiaoli Z. Fern, Hamed Shahbazi, Prasad Tadepalli
2018	A*	`conf`	Emergency Response Optimization using Online Hybrid Planning. IJCAI Durga Harish Dayapule, Aswin Raghavan, Prasad Tadepalli, Alan Fern
2018	A*	`conf`	Event Detection with Neural Networks: A Rigorous Empirical Evaluation. EMNLP John Walker Orr, Prasad Tadepalli, Xiaoli Z. Fern
2018	J	`jnl`	Event Detection with Neural Networks: A Rigorous Empirical Evaluation. CoRR John Walker Orr, Prasad Tadepalli, Xiaoli Z. Fern
2018	J	`jnl`	Event Nugget Detection with Forward-Backward Recurrent Neural Networks. CoRR Reza Ghaeini, Xiaoli Z. Fern, Liang Huang, Prasad Tadepalli
2018	J	`jnl`	Interactive Naming for Explaining Deep Neural Networks: A Formative Study. CoRR Mandana Hamidi-Haines, Zhongang Qi, Alan Fern, Fuxin Li, Prasad Tadepalli
2018	A*	`conf`	Interpreting Recurrent and Attention-Based Neural Models: a Case Study on Natural Language Inference. EMNLP Reza Ghaeini, Xiaoli Z. Fern, Prasad Tadepalli
2018	J	`jnl`	Interpreting Recurrent and Attention-Based Neural Models: a Case Study on Natural Language Inference. CoRR Reza Ghaeini, Xiaoli Z. Fern, Prasad Tadepalli
2018	B	`conf`	Joint Neural Entity Disambiguation with Output Space Search. COLING Hamed Shahbazi, Xiaoli Z. Fern, Reza Ghaeini, Chao Ma, Rasha Mohammad Obeidat, Prasad Tadepalli
2018	J	`jnl`	Joint Neural Entity Disambiguation with Output Space Search. CoRR Hamed Shahbazi, Xiaoli Z. Fern, Reza Ghaeini, Chao Ma, Rasha Obeidat, Prasad Tadepalli
2018	J	`jnl`	Learning Scripts as Hidden Markov Models. CoRR John Walker Orr, Prasad Tadepalli, Janardhan Rao Doppa, Xiaoli Z. Fern, Thomas G. Dietterich
2018	A*	`conf`	Training Deep Reactive Policies for Probabilistic Planning Problems. ICAPS Murugeswari Issakkimuthu, Alan Fern, Prasad Tadepalli
2017	B	`conf`	Adaptive Submodularity with Varying Query Sets: An Application to Active Multi-label Learning. ALT Alan Fern, Robby Goetschalckx, Mandana Hamidi-Haines, Prasad Tadepalli
2017	—	`ch.`	Average-Reward Reinforcement Learning. Encyclopedia of Machine Learning and Data Mining Prasad Tadepalli
2017	A*	`conf`	Hindsight Optimization for Hybrid State and Action MDPs. AAAI Aswin Raghavan, Scott Sanner, Roni Khardon, Prasad Tadepalli, Alan Fern
2017	—	`ch.`	Model-Based Reinforcement Learning. Encyclopedia of Machine Learning and Data Mining Soumya Ray, Prasad Tadepalli
2017	C	`conf`	Multi-Task Structured Prediction for Entity Analysis: Search-Based Learning Algorithms. ACML Chao Ma, Janardhan Rao Doppa, Prasad Tadepalli, Hamed Shahbazi, Xiaoli Z. Fern
2016	—	`conf`	Cross Lingual Mention and Entity Embeddings for Cross-Lingual Entity Disambiguation. TAC Hamed Shahbazi, Chao Ma, Xiaoli Z. Fern, Prasad Tadepalli
2016	—	`conf`	Event Nugget Detection with Forward-Backward Recurrent Neural Networks. ACL (2) Reza Ghaeini, Xiaoli Z. Fern, Liang Huang, Prasad Tadepalli
2016	—	`conf`	Label Embedding Approach for Transfer Learning. ICBO/BioCreative Rasha Obeidat, Xiaoli Z. Fern, Prasad Tadepalli
2015	A*	`conf`	Active Imitation Learning of Hierarchical Policies. IJCAI Mandana Hamidi, Prasad Tadepalli, Robby Goetschalckx, Alan Fern
2015	A*	`conf`	Factored MCTS for Large Scale Stochastic Planning. AAAI Hao Cui, Roni Khardon, Alan Fern, Prasad Tadepalli
2015	A*	`conf`	Hindsight Optimization for Probabilistic Planning with Factored Actions. ICAPS Murugeswari Issakkimuthu, Alan Fern, Roni Khardon, Prasad Tadepalli, Shan Xue
2015	A*	`conf`	Learning Greedy Policies for the Easy-First Framework. AAAI Jun Xie, Chao Ma, Janardhan Rao Doppa, Prashanth Mannem, Xiaoli Z. Fern, Thomas G. Dietterich, Prasad Tadepalli
2015	A	`conf`	Memory-Effcient Symbolic Online Planning for Factored MDPs. UAI Aswin Raghavan, Roni Khardon, Prasad Tadepalli, Alan Fern
2015	A*	`conf`	Multitask Coactive Learning. IJCAI Robby Goetschalckx, Alan Fern, Prasad Tadepalli
2014	J	`jnl`	A Decision-Theoretic Model of Assistance. J. Artif. Intell. Res. Alan Fern, Sriraam Natarajan, Kshitij Judah, Prasad Tadepalli
2014	J	`jnl`	Active lmitation learning: formal and practical reductions to I.I.D. learning. J. Mach. Learn. Res. Kshitij Judah, Alan Paul Fern, Thomas G. Dietterich, Prasad Tadepalli
2014	A*	`conf`	Coactive Learning for Locally Optimal Problem Solving. AAAI Robby Goetschalckx, Alan Fern, Prasad Tadepalli
2014	J	`jnl`	Coactive Learning for Locally Optimal Problem Solving. CoRR Robby Goetschalckx, Alan Fern, Prasad Tadepalli
2014	A*	`conf`	HC-Search for Multi-Label Prediction: An Empirical Study. AAAI Janardhan Rao Doppa, Jun Yu, Chao Ma, Alan Fern, Prasad Tadepalli
2014	J	`jnl`	HC-Search: A Learning Framework for Search-based Structured Prediction. J. Artif. Intell. Res. Janardhan Rao Doppa, Alan Fern, Prasad Tadepalli
2014	A*	`conf`	Imitation Learning with Demonstrations and Shaping Rewards. AAAI Kshitij Judah, Alan Fern, Prasad Tadepalli, Robby Goetschalckx
2014	A*	`conf`	Learning Scripts as Hidden Markov Models. AAAI John Walker Orr, Prasad Tadepalli, Janardhan Rao Doppa, Xiaoli Z. Fern, Thomas G. Dietterich
2014	A*	`conf`	Prune-and-Score: Learning for Greedy Coreference Resolution. EMNLP Chao Ma, Janardhan Rao Doppa, John Walker Orr, Prashanth Mannem, Xiaoli Z. Fern, Thomas G. Dietterich, Prasad Tadepalli
2014	J	`jnl`	Structured prediction via output space search. J. Mach. Learn. Res. Janardhan Rao Doppa, Alan Fern, Prasad Tadepalli
2014	J	`jnl`	Using trajectory data to improve bayesian optimization for reinforcement learning. J. Mach. Learn. Res. Aaron Wilson, Alan Fern, Prasad Tadepalli
2013	B	`conf`	Accelerating Imitation Learning in Relational Domains via Transfer by Initialization. ILP Sriraam Natarajan, Phillip Odom, Saket Joshi, Tushar Khot, Kristian Kersting, Prasad Tadepalli
2013	A*	`conf`	HC-Search: Learning Heuristics and Cost Functions for Structured Prediction. AAAI Janardhan Rao Doppa, Alan Fern, Prasad Tadepalli
2013	—	`conf`	Relational Markov Decision Processes: Promise and Prospects. StarAI@AAAI Saket Joshi, Roni Khardon, Prasad Tadepalli, Alan Fern, Aswin Raghavan
2013	—	`conf`	Solving Relational MDPs with Exogenous Events and Additive Rewards. ECML/PKDD (1) Saket Joshi, Roni Khardon, Prasad Tadepalli, Aswin Raghavan, Alan Fern
2013	J	`jnl`	Solving Relational MDPs with Exogenous Events and Additive Rewards. CoRR Saket Joshi, Roni Khardon, Prasad Tadepalli, Aswin Raghavan, Alan Fern
2013	—	`conf`	Symbolic Opportunistic Policy Iteration for Factored-Action MDPs. NIPS Aswin Raghavan, Roni Khardon, Alan Fern, Prasad Tadepalli
2012	—	`conf`	A Bayesian Approach for Policy Learning from Trajectory Preference Queries. NIPS Aaron Wilson, Alan Fern, Prasad Tadepalli
2012	J	`jnl`	A relational hierarchical model for decision-theoretic assistance. Knowl. Inf. Syst. Sriraam Natarajan, Prasad Tadepalli, Alan Fern
2012	—	`conf`	Accelarating Imitation Learning in Relational Domains via Transfer by Initialization. StarAI@UAI Sriraam Natarajan, Phillip Odom, Saket Joshi, Tushar Khot, Kristian Kersting, Prasad Tadepalli
2012	J	`jnl`	An Ensemble Architecture for Learning Complex Problem-Solving Techniques from Demonstration. ACM Trans. Intell. Syst. Technol. Xiaoqin Zhang, Bhavesh Shrestha, Sung Wook Yoon, Subbarao Kambhampati, Phillip DiBona, Jinhong K. Guo, Daniel McFarlane, Martin O. Hofmann, Kenneth R. Whitebread, Darren Scott Appling, Elizabeth T. Whitaker, Ethan Trewhitt, Li Ding, James Michaelis, Deborah L. McGuinness, James A. Hendler, Janardhan Rao Doppa, Charles Parker, Thomas G. Dietterich, Prasad Tadepalli, Weng-Keen Wong, Derek T. Green, Antons Rebguns, Diana F. Spears, Ugur Kuter, Geoffrey Levine, Gerald DeJong, Reid MacTavish, Santiago Ontañón, Jainarayan Radhakrishnan, Ashwin Ram, Hala Mostafa, Huzaifa Zafar, Chongjie Zhang, Daniel D. Corkill, Victor R. Lesser, Zhexuan Song
2012	A*	`conf`	Output Space Search for Structured Prediction. ICML Janardhan Rao Doppa, Alan Fern, Prasad Tadepalli
2012	A*	`conf`	Planning in Factored Action Spaces with Symbolic Dynamic Programming. AAAI Aswin Raghavan, Saket Joshi, Alan Fern, Prasad Tadepalli, Roni Khardon
2012	—	`conf`	Transfer Learning in Sequential Decision Problems: A Hierarchical Bayesian Approach. ICML Unsupervised and Transfer Learning Aaron Wilson, Alan Fern, Prasad Tadepalli
2011	J	`jnl`	Automatic Discovery and Transfer of Task Hierarchies in Reinforcement Learning. AI Mag. Neville Mehta, Soumya Ray, Prasad Tadepalli, Thomas G. Dietterich
2011	—	`conf`	Autonomous Learning of Action Models for Planning. NIPS Neville Mehta, Prasad Tadepalli, Alan Fern
2011	A*	`conf`	Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach. IJCAI Sriraam Natarajan, Saket Joshi, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik
2011	—	`conf`	Inverting Grice's Maxims to Learn Rules from Natural Language Extractions. NIPS Shahed Sorower, Thomas G. Dietterich, Janardhan Rao Doppa, John Walker Orr, Prasad Tadepalli, Xiaoli Z. Fern
2011	C	`conf`	Learning Rules from Incomplete Examples via Implicit Mention Models. ACML Janardhan Rao Doppa, Shahed Sorower, Mohammad NasrEsfahani, John Walker Orr, Thomas G. Dietterich, Xiaoli Z. Fern, Prasad Tadepalli, Jed Irvine
2011	J	`jnl`	The first learning track of the international planning competition. Mach. Learn. Alan Fern, Roni Khardon, Prasad Tadepalli
2010	—	`conf`	A Computational Decision Theory for Interactive Assistants. Interactive Decision Theory and Game Theory Alan Fern, Prasad Tadepalli
2010	—	`conf`	A Computational Decision Theory for Interactive Assistants. NIPS Alan Fern, Prasad Tadepalli
2010	—	`ch.`	Average-Reward Reinforcement Learning. Encyclopedia of Machine Learning Prasad Tadepalli
2010	A*	`conf`	Bayesian Policy Search for Multi-Agent Role Discovery. AAAI Aaron Wilson, Alan Fern, Prasad Tadepalli
2010	A	`conf`	Bayesian role discovery for multi-agent reinforcement learning. AAMAS Aaron Wilson, Alan Fern, Prasad Tadepalli
2010	—	`conf`	Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models. StarAI@AAAI Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik
2010	—	`conf`	Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models. ECML/PKDD (2) Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik
2010	—	`conf`	Incorporating Domain Models into Bayesian Optimization for RL. ECML/PKDD (3) Aaron Wilson, Alan Fern, Prasad Tadepalli
2010	—	`conf`	Learning Algorithms for Link Prediction Based on Chance Constraints. ECML/PKDD (1) Janardhan Rao Doppa, Jun Yu, Prasad Tadepalli, Lise Getoor
2010	—	`ch.`	Model-Based Reinforcement Learning. Encyclopedia of Machine Learning Soumya Ray, Prasad Tadepalli
2010	C	`conf`	Multi-Agent Inverse Reinforcement Learning. ICMLA Sriraam Natarajan, Gautam Kunapuli, Kshitij Judah, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik
2009	C	`conf`	An Ensemble Learning and Problem Solving Architecture for Airspace Management. IAAI Xiaoqin Zhang, Sung Wook Yoon, Phillip DiBona, Darren Scott Appling, Li Ding, Janardhan Rao Doppa, Derek T. Green, Jinhong K. Guo, Ugur Kuter, Geoffrey Levine, Reid MacTavish, Daniel McFarlane, James Michaelis, Hala Mostafa, Santiago Ontañón, Charles Parker, Jainarayan Radhakrishnan, Antons Rebguns, Bhavesh Shrestha, Zhexuan Song, Ethan Trewhitt, Huzaifa Zafar, Chongjie Zhang, Daniel D. Corkill, Gerald DeJong, Thomas G. Dietterich, Subbarao Kambhampati, Victor R. Lesser, Deborah L. McGuinness, Ashwin Ram, Diana F. Spears, Prasad Tadepalli, Elizabeth T. Whitaker, Weng-Keen Wong, James A. Hendler, Martin O. Hofmann, Kenneth R. Whitebread
2009	J	`jnl`	Guest editorial: special issue on structured prediction. Mach. Learn. Charles Parker, Yasemin Altun, Prasad Tadepalli
2009	—	`conf`	Knowledge Intensive Learning - Directed vs Undirected SRL Models. MLG/SRL@ILP Sriraam Natarajan, Prasad Tadepalli, Gautam Kunapuli, Jude W. Shavlik
2009	C	`conf`	Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule. ICMLA Sriraam Natarajan, Prasad Tadepalli, Gautam Kunapuli, Jude W. Shavlik
2009	A*	`conf`	Lower Bounding Klondike Solitaire with Monte-Carlo Planning. ICAPS Ronald Bjarnason, Alan Fern, Prasad Tadepalli
2009	C	`conf`	Multiagent Transfer Learning via Assignment-Based Decomposition. ICMLA Scott Proper, Prasad Tadepalli
2009	C	`conf`	Simulation-based Optimization of Resource Placement and Emergency Response. IAAI Ronald Bjarnason, Prasad Tadepalli, Alan Fern, Carl Niedner
2009	—	`conf`	Solving multiagent assignment Markov decision processes. AAMAS (1) Scott Proper, Prasad Tadepalli
2009	B	`conf`	Transfer Learning via Relational Templates. ILP Scott Proper, Prasad Tadepalli
2008	A*	`conf`	Automatic discovery and transfer of MAXQ hierarchies. ICML Neville Mehta, Soumya Ray, Prasad Tadepalli, Thomas G. Dietterich
2008	J	`jnl`	Guest editors' introduction: special issue on inductive logic programming (ILP-2007). Mach. Learn. Hendrik Blockeel, Jude W. Shavlik, Prasad Tadepalli
2008	B	`ed.`	Inductive Logic Programming, 17th International Conference, ILP 2007, Corvallis, OR, USA, June 19-21, 2007, Revised Selected Papers ILP Hendrik Blockeel, Jan Ramon, Jude W. Shavlik, Prasad Tadepalli
2008	J	`jnl`	Learning first-order probabilistic models with combining rules. Ann. Math. Artif. Intell. Sriraam Natarajan, Prasad Tadepalli, Thomas G. Dietterich, Alan Fern
2008	J	`jnl`	Learning to Solve Problems from Exercises. Comput. Intell. Prasad Tadepalli
2008	B	`conf`	Logical Hierarchical Hidden Markov Models for Modeling User Activities. ILP Sriraam Natarajan, Hung Hai Bui, Prasad Tadepalli, Kristian Kersting, Weng-Keen Wong
2008	J	`jnl`	Structured machine learning: the next ten years. Mach. Learn. Thomas G. Dietterich, Pedro M. Domingos, Lise Getoor, Stephen H. Muggleton, Prasad Tadepalli
2008	J	`jnl`	Transfer in variable-reward hierarchical reinforcement learning. Mach. Learn. Neville Mehta, Sriraam Natarajan, Prasad Tadepalli, Alan Fern
2007	—	`conf`	A Decision-Theoretic Model of Assistance - Evaluation, Extensions and Open Problems. AAAI Spring Symposium: Interaction Challenges for Intelligent Assistants Sriraam Natarajan, Kshitij Judah, Prasad Tadepalli, Alan Fern
2007	—	`conf`	A Decision-Theoretic Model of Assistance - Evaluation, Extensions and Open Problems. Interaction Challenges for Intelligent Assistants Sriraam Natarajan, Kshitij Judah, Prasad Tadepalli, Alan Fern
2007	A*	`conf`	A Decision-Theoretic Model of Assistance. IJCAI Alan Fern, Sriraam Natarajan, Kshitij Judah, Prasad Tadepalli
2007	B	`conf`	A Relational Hierarchical Model for Decision-Theoretic Assistance. ILP Sriraam Natarajan, Prasad Tadepalli, Alan Fern
2007	—	`conf`	Exploiting prior knowledge in Intelligent Assistants - Combining relational models with hierarchies. Probabilistic, Logical and Relational Learning - A Further Synthesis Sriraam Natarajan, Prasad Tadepalli, Alan Fern
2007	A*	`conf`	Learning for efficient retrieval of structured data with noisy queries. ICML Charles Parker, Alan Fern, Prasad Tadepalli
2007	A*	`conf`	Multi-task reinforcement learning: a hierarchical Bayesian approach. ICML Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepalli
2007	J	`jnl`	Searching Solitaire in Real Time. ICGA J. Ronald Bjarnason, Prasad Tadepalli, Alan Fern
2006	A*	`conf`	Gradient Boosting for Sequence Alignment. AAAI Charles Parker, Alan Fern, Prasad Tadepalli
2006	—	`conf`	Scaling Model-Based Average-Reward Reinforcement Learning for Product Delivery. ECML Scott Proper, Prasad Tadepalli
2005	A*	`conf`	Dynamic preferences in multi-criteria reinforcement learning. ICML Sriraam Natarajan, Prasad Tadepalli
2005	A*	`conf`	Learning first-order probabilistic models with combining rules. ICML Sriraam Natarajan, Prasad Tadepalli, Eric Altendorf, Thomas G. Dietterich, Alan Fern, Angelo C. Restificar
2002	A*	`conf`	Learning Decision Rules by Randomized Iterative Local Search. ICML Michael Chisholm, Prasad Tadepalli
2002	A*	`conf`	Model-based Hierarchical Average-reward Reinforcement Learning. ICML Sandeep Seri, Prasad Tadepalli
2001	J	`jnl`	On Exact Learning of Unordered Tree Patterns. Mach. Learn. Thomas R. Amoth, Paul Cull, Prasad Tadepalli
1999	A*	`conf`	Exact Learning of Unordered Tree Patterns from Queries. COLT Thomas R. Amoth, Paul Cull, Prasad Tadepalli
1999	J	`jnl`	Learning Horn Definitions: Theory and an Application to Planning. New Gener. Comput. Chandra Reddy, Prasad Tadepalli
1998	A*	`conf`	Exact Learning of Tree Patterns from Queries and Counterexamples. COLT Thomas R. Amoth, Paul Cull, Prasad Tadepalli
1998	A*	`conf`	Learning First-Order Acyclic Horn Programs from Entailment. ICML Chandra Reddy, Prasad Tadepalli
1998	B	`conf`	Learning First-Order Acyclic Horn Programs from Entailment. ILP Chandra Reddy, Prasad Tadepalli
1998	J	`jnl`	Learning from Examples and Membership Queries with Structured Determinations. Mach. Learn. Prasad Tadepalli, Stuart Russell
1998	J	`jnl`	Model-Based Average Reward Reinforcement Learning. Artif. Intell. Prasad Tadepalli, DoKyeong Ok
1997	—	`conf`	Active Learning with Committees for Text Categorization. AAAI/IAAI Ray Liere, Prasad Tadepalli
1997	—	`conf`	Active Learning with Committees. AAAI/IAAI Ray Liere, Prasad Tadepalli
1997	A*	`conf`	Hierarchical Explanation-Based Reinforcement Learning. ICML Prasad Tadepalli, Thomas G. Dietterich
1997	—	`conf`	Learning Goal-Decomposition Rules Using Exercises. AAAI/IAAI Chandra Reddy, Prasad Tadepalli
1997	A*	`conf`	Learning Goal-Decomposition Rules using Exercises. ICML Chandra Reddy, Prasad Tadepalli
1997	B	`conf`	Learning Horn Definitions with Equivalence and Membership Queries. ILP Chandra Reddy, Prasad Tadepalli
1996	J	`jnl`	A Formal Framework for Speedup Learning from Problems and Solutions CoRR Prasad Tadepalli, Balas K. Natarajan
1996	J	`jnl`	A Formal Framework for Speedup Learning from Problems and Solutions. J. Artif. Intell. Res. Prasad Tadepalli, Balas K. Natarajan
1996	—	`conf`	Auto-Exploratory Average Reward Reinforcement Learning. AAAI/IAAI, Vol. 1 DoKyeong Ok, Prasad Tadepalli
1996	A*	`conf`	Scaling Up Average Reward Reinforcement Learning by Approximating the Domain Models and the Value Function. ICML Prasad Tadepalli, DoKyeong Ok
1996	A*	`conf`	Theory-guided Empirical Speedup Learning of Goal Decomposition Rules. ICML Chandra Reddy, Prasad Tadepalli, Silvana Roncagliolo
1994	J	`jnl`	Quantifying Prior Determination Knowledge Using the PAC Learning Model. Mach. Learn. Sridhar Mahadevan, Prasad Tadepalli
1993	J	`jnl`	An Apprentice-Based Approach to Knowledge Acquisition. Artif. Intell. Sridhar Mahadevan, Tom M. Mitchell, Jack Mostow, Louis I. Steinberg, Prasad Tadepalli
1993	A*	`conf`	Learning from Queries and Examples with Tree-structured Bias. ICML Prasad Tadepalli
1992	A*	`conf`	A Theory of Unsupervised Speedup Learning. AAAI Prasad Tadepalli
1991	A*	`conf`	A Formalization of Explanation-Based Macro-operator Learning. IJCAI Prasad Tadepalli
1991	—	`conf`	Learning with Incrutable Theories. ML Prasad Tadepalli
1990	J	`jnl`	Maximizing the Predictive Value of Production Rules. Artif. Intell. Sholom M. Weiss, Robert S. Galen, Prasad Tadepalli
1989	A*	`conf`	Lazy ExplanationBased Learning: A Solution to the Intractable Theory Problem. IJCAI Prasad Tadepalli
1989	—	`conf`	Planning Approximate Plans for Use in the Real World. ML Prasad Tadepalli
1988	—	`conf`	On the Tractability of Learning from Incomplete Theories. ML Sridhar Mahadevan, Prasad Tadepalli
1988	—	`conf`	Two New Frameworks for Learning. ML Balas K. Natarajan, Prasad Tadepalli
1987	A*	`conf`	Optimizing the Predictive Value of Diagnostic Decision Rules. AAAI Sholom M. Weiss, Robert S. Galen, Prasad Tadepalli