Prasad Tadepalli

According to our database1, Prasad Tadepalli authored at least 118 papers between 1987 and 2019.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

Homepage:

On csauthors.net:

Bibliography

2019
Description-Based Zero-shot Fine-Grained Entity Typing.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Saliency Learning: Teaching the Model Where to Pay Attention.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Interactive Naming for Explaining Deep Neural Networks: A Formative Study.
Proceedings of the Joint Proceedings of the ACM IUI 2019 Workshops co-located with the 24th ACM Conference on Intelligent User Interfaces (ACM IUI 2019), 2019

2018
Emergency Response Optimization using Online Hybrid Planning.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Event Detection with Neural Networks: A Rigorous Empirical Evaluation.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Interpreting Recurrent and Attention-Based Neural Models: a Case Study on Natural Language Inference.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Joint Neural Entity Disambiguation with Output Space Search.
Proceedings of the 27th International Conference on Computational Linguistics, 2018

Dependent Gated Reading for Cloze-Style Question Answering.
Proceedings of the 27th International Conference on Computational Linguistics, 2018

Training Deep Reactive Policies for Probabilistic Planning Problems.
Proceedings of the Twenty-Eighth International Conference on Automated Planning and Scheduling, 2018

2017
Average-Reward Reinforcement Learning.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Model-Based Reinforcement Learning.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Adaptive Submodularity with Varying Query Sets: An Application to Active Multi-label Learning.
Proceedings of the International Conference on Algorithmic Learning Theory, 2017

Multi-Task Structured Prediction for Entity Analysis: Search-Based Learning Algorithms.
Proceedings of The 9th Asian Conference on Machine Learning, 2017

Hindsight Optimization for Hybrid State and Action MDPs.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Cross Lingual Mention and Entity Embeddings for Cross-Lingual Entity Disambiguation.
Proceedings of the 2016 Text Analysis Conference, 2016

Label Embedding Approach for Transfer Learning.
Proceedings of the Joint International Conference on Biological Ontology and BioCreative, 2016

Event Nugget Detection with Forward-Backward Recurrent Neural Networks.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

2015
Memory-Effcient Symbolic Online Planning for Factored MDPs.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Active Imitation Learning of Hierarchical Policies.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Multitask Coactive Learning.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Hindsight Optimization for Probabilistic Planning with Factored Actions.
Proceedings of the Twenty-Fifth International Conference on Automated Planning and Scheduling, 2015

Learning Greedy Policies for the Easy-First Framework.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Factored MCTS for Large Scale Stochastic Planning.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Using trajectory data to improve bayesian optimization for reinforcement learning.
J. Mach. Learn. Res., 2014

Active lmitation learning: formal and practical reductions to I.I.D. learning.
J. Mach. Learn. Res., 2014

Structured prediction via output space search.
J. Mach. Learn. Res., 2014

HC-Search: A Learning Framework for Search-based Structured Prediction.
J. Artif. Intell. Res., 2014

Prune-and-Score: Learning for Greedy Coreference Resolution.
Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, 2014

Learning Scripts as Hidden Markov Models.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

Imitation Learning with Demonstrations and Shaping Rewards.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

Coactive Learning for Locally Optimal Problem Solving.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

HC-Search for Multi-Label Prediction: An Empirical Study.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Solving Relational MDPs with Exogenous Events and Additive Rewards.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Symbolic Opportunistic Policy Iteration for Factored-Action MDPs.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Accelerating Imitation Learning in Relational Domains via Transfer by Initialization.
Proceedings of the Inductive Logic Programming - 23rd International Conference, 2013

Relational Markov Decision Processes: Promise and Prospects.
Proceedings of the Statistical Relational Artificial Intelligence, 2013

HC-Search: Learning Heuristics and Cost Functions for Structured Prediction.
Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013

2012
An Ensemble Architecture for Learning Complex Problem-Solving Techniques from Demonstration.
ACM TIST, 2012

Transfer Learning in Sequential Decision Problems: A Hierarchical Bayesian Approach.
Proceedings of the Unsupervised and Transfer Learning, 2012

A Bayesian Approach for Policy Learning from Trajectory Preference Queries.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Output Space Search for Structured Prediction.
Proceedings of the 29th International Conference on Machine Learning, 2012

Planning in Factored Action Spaces with Symbolic Dynamic Programming.
Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011
The first learning track of the international planning competition.
Machine Learning, 2011

Learning Rules from Incomplete Examples via Implicit Mention Models.
Proceedings of the 3rd Asian Conference on Machine Learning, 2011

Automatic Discovery and Transfer of Task Hierarchies in Reinforcement Learning.
AI Magazine, 2011

Inverting Grice's Maxims to Learn Rules from Natural Language Extractions.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Autonomous Learning of Action Models for Planning.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach.
Proceedings of the IJCAI 2011, 2011

2010
Average-Reward Reinforcement Learning.
Proceedings of the Encyclopedia of Machine Learning, 2010

Model-Based Reinforcement Learning.
Proceedings of the Encyclopedia of Machine Learning, 2010

Incorporating Domain Models into Bayesian Optimization for RL.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Learning Algorithms for Link Prediction Based on Chance Constraints.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

A Computational Decision Theory for Interactive Assistants.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Multi-Agent Inverse Reinforcement Learning.
Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

Bayesian role discovery for multi-agent reinforcement learning.
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), 2010

Bayesian Policy Search for Multi-Agent Role Discovery.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models.
Proceedings of the Statistical Relational Artificial Intelligence, 2010

A Computational Decision Theory for Interactive Assistants.
Proceedings of the Interactive Decision Theory and Game Theory, 2010

2009
Guest editorial: special issue on structured prediction.
Machine Learning, 2009

Transfer Learning via Relational Templates.
Proceedings of the Inductive Logic Programming, 19th International Conference, 2009

Multiagent Transfer Learning via Assignment-Based Decomposition.
Proceedings of the International Conference on Machine Learning and Applications, 2009

Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule.
Proceedings of the International Conference on Machine Learning and Applications, 2009


Simulation-based Optimization of Resource Placement and Emergency Response.
Proceedings of the Twenty-First Conference on Innovative Applications of Artificial Intelligence, 2009

Solving multiagent assignment Markov decision processes.
Proceedings of the 8th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2009), 2009

Lower Bounding Klondike Solitaire with Monte-Carlo Planning.
Proceedings of the 19th International Conference on Automated Planning and Scheduling, 2009

2008
Transfer in variable-reward hierarchical reinforcement learning.
Machine Learning, 2008

Structured machine learning: the next ten years.
Machine Learning, 2008

Guest editors' introduction: special issue on inductive logic programming (ILP-2007).
Machine Learning, 2008

Learning to Solve Problems from Exercises.
Computational Intelligence, 2008

Learning first-order probabilistic models with combining rules.
Ann. Math. Artif. Intell., 2008

Logical Hierarchical Hidden Markov Models for Modeling User Activities.
Proceedings of the Inductive Logic Programming, 18th International Conference, 2008

Automatic discovery and transfer of MAXQ hierarchies.
Proceedings of the Machine Learning, 2008

2007
Searching Solitaire in Real Time.
ICGA Journal, 2007

A Relational Hierarchical Model for Decision-Theoretic Assistance.
Proceedings of the Inductive Logic Programming, 17th International Conference, 2007

A Decision-Theoretic Model of Assistance.
Proceedings of the IJCAI 2007, 2007

Multi-task reinforcement learning: a hierarchical Bayesian approach.
Proceedings of the Machine Learning, 2007

Learning for efficient retrieval of structured data with noisy queries.
Proceedings of the Machine Learning, 2007

A Decision-Theoretic Model of Assistance - Evaluation, Extensions and Open Problems.
Proceedings of the Interaction Challenges for Intelligent Assistants, 2007

Exploiting prior knowledge in Intelligent Assistants - Combining relational models with hierarchies.
Proceedings of the Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04., 2007

A Decision-Theoretic Model of Assistance - Evaluation, Extensions and Open Problems.
Proceedings of the Interaction Challenges for Intelligent Assistants, 2007

2006
Scaling Model-Based Average-Reward Reinforcement Learning for Product Delivery.
Proceedings of the Machine Learning: ECML 2006, 2006

Gradient Boosting for Sequence Alignment.
Proceedings of the Proceedings, 2006

2005
Learning first-order probabilistic models with combining rules.
Proceedings of the Machine Learning, 2005

Dynamic preferences in multi-criteria reinforcement learning.
Proceedings of the Machine Learning, 2005

2002
Model-based Hierarchical Average-reward Reinforcement Learning.
Proceedings of the Machine Learning, 2002

Learning Decision Rules by Randomized Iterative Local Search.
Proceedings of the Machine Learning, 2002

2001
On Exact Learning of Unordered Tree Patterns.
Machine Learning, 2001

1999
Learning Horn Definitions: Theory and an Application to Planning.
New Generation Comput., 1999

Exact Learning of Unordered Tree Patterns from Queries.
Proceedings of the Twelfth Annual Conference on Computational Learning Theory, 1999

1998
Learning from Examples and Membership Queries with Structured Determinations.
Machine Learning, 1998

Model-Based Average Reward Reinforcement Learning.
Artif. Intell., 1998

Learning First-Order Acyclic Horn Programs from Entailment.
Proceedings of the Inductive Logic Programming, 8th International Workshop, 1998

Learning First-Order Acyclic Horn Programs from Entailment.
Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998

Exact Learning of Tree Patterns from Queries and Counterexamples.
Proceedings of the Eleventh Annual Conference on Computational Learning Theory, 1998

1997
Learning Horn Definitions with Equivalence and Membership Queries.
Proceedings of the Inductive Logic Programming, 7th International Workshop, 1997

Hierarchical Explanation-Based Reinforcement Learning.
Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997

Learning Goal-Decomposition Rules using Exercises.
Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997

Learning Goal-Decomposition Rules Using Exercises.
Proceedings of the Fourteenth National Conference on Artificial Intelligence and Ninth Innovative Applications of Artificial Intelligence Conference, 1997

Active Learning with Committees.
Proceedings of the Fourteenth National Conference on Artificial Intelligence and Ninth Innovative Applications of Artificial Intelligence Conference, 1997

Active Learning with Committees for Text Categorization.
Proceedings of the Fourteenth National Conference on Artificial Intelligence and Ninth Innovative Applications of Artificial Intelligence Conference, 1997

1996
A Formal Framework for Speedup Learning from Problems and Solutions.
J. Artif. Intell. Res., 1996

Scaling Up Average Reward Reinforcement Learning by Approximating the Domain Models and the Value Function.
Proceedings of the Machine Learning, 1996

Theory-guided Empirical Speedup Learning of Goal Decomposition Rules.
Proceedings of the Machine Learning, 1996

Auto-Exploratory Average Reward Reinforcement Learning.
Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 1996

1994
Quantifying Prior Determination Knowledge Using the PAC Learning Model.
Machine Learning, 1994

1993
An Apprentice-Based Approach to Knowledge Acquisition.
Artif. Intell., 1993

Learning from Queries and Examples with Tree-structured Bias.
Proceedings of the Machine Learning, 1993

1992
A Theory of Unsupervised Speedup Learning.
Proceedings of the 10th National Conference on Artificial Intelligence, 1992

1991
A Formalization of Explanation-Based Macro-operator Learning.
Proceedings of the 12th International Joint Conference on Artificial Intelligence. Sydney, 1991

Learning with Incrutable Theories.
Proceedings of the Eighth International Workshop (ML91), 1991

1990
Maximizing the Predictive Value of Production Rules.
Artif. Intell., 1990

1989
Lazy ExplanationBased Learning: A Solution to the Intractable Theory Problem.
Proceedings of the 11th International Joint Conference on Artificial Intelligence. Detroit, 1989

Planning Approximate Plans for Use in the Real World.
Proceedings of the Sixth International Workshop on Machine Learning (ML 1989), 1989

1988
Two New Frameworks for Learning.
Proceedings of the Machine Learning, 1988

On the Tractability of Learning from Incomplete Theories.
Proceedings of the Machine Learning, 1988

1987
Optimizing the Predictive Value of Diagnostic Decision Rules.
Proceedings of the 6th National Conference on Artificial Intelligence. Seattle, 1987


  Loading...