Prasad Tadepalli

Balaraman Ravindran

Neural Comput. Appl., August, 2023

Global Explanations for Image Classifiers (Student Abstract).

[BibT_eX]

[DOI]

Bhavan K. Vasu

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Formalizing the Problem of Side Effect Regularization.

[BibT_eX]

[DOI]

Aseem Saxena

CoRR, 2022

Parametrically Retargetable Decision-Makers Tend To Seek Power.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Hybrid Deep RePReL: Integrating Relational Planning and Reinforcement Learning for Information Fusion.

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on Information Fusion, 2022

2021

Dynamic probabilistic logic models for effective abstractions in RL.

[BibT_eX]

[DOI]

CoRR, 2021

From Heatmaps to Structural Explanations of Image Classifiers.

[BibT_eX]

[DOI]

CoRR, 2021

Optimal Policies Tend To Seek Power.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

One Explanation is Not Enough: Structured Attention Graphs for Image Classification.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

DeepAveragers: Offline Reinforcement Learning By Solving Derived Non-Parametric MDPs.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Improving Multilingual Translation by Representation and Gradient Regularization.

[BibT_eX]

[DOI]

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction.

[BibT_eX]

[DOI]

Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling, 2021

PAC Learning of Causal Trees with Latent Variables.

[BibT_eX]

[DOI]

Stuart J. Russell

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Structured Attention Graphs for Understanding Deep Image Classifications.

[BibT_eX]

[DOI]

CoRR, 2020

Avoiding Side Effects in Complex Environments.

[BibT_eX]

[DOI]

Neale Ratzlaff

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

On the Sub-Layer Functionalities of Transformer Decoder.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Conservative Agency via Attainable Utility Preservation.

[BibT_eX]

[DOI]

Dylan Hadfield-Menell

Proceedings of the AIES '20: AAAI/ACM Conference on AI, 2020

Relation Extraction with Explanation.

[BibT_eX]

[DOI]

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

The Choice Function Framework for Online Policy Improvement.

[BibT_eX]

[DOI]

Murugeswari Issakkimuthu

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Entity-aware ELMo: Learning Contextual Entity Representation for Entity Disambiguation.

[BibT_eX]

[DOI]

CoRR, 2019

Reports of the AAAI 2019 Spring Symposium Series.

[BibT_eX]

[DOI]

AI Mag., 2019

Optimizing Earth Moving Operations Via Reinforcement Learning.

[BibT_eX]

[DOI]

Vivswan Shitole

Joseph Louis

Proceedings of the 2019 Winter Simulation Conference, 2019

Description-Based Zero-shot Fine-Grained Entity Typing.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Mandana Hamidi-Haines

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

Conservative Agency.

[BibT_eX]

[DOI]

Dylan Hadfield-Menell

Proceedings of the Workshop on Artificial Intelligence Safety 2019 co-located with the 28th International Joint Conference on Artificial Intelligence, 2019

2018

Attentional Multi-Reading Sarcasm Detection.

[BibT_eX]

[DOI]

Reza Ghaeini

CoRR, 2018

Emergency Response Optimization using Online Hybrid Planning.

[BibT_eX]

[DOI]

Durga Harish Dayapule

Aswin Raghavan

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Event Detection with Neural Networks: A Rigorous Empirical Evaluation.

[BibT_eX]

[DOI]

John Walker Orr

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.

[BibT_eX]

[DOI]

Reza Ghaeini

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.

[BibT_eX]

[DOI]

Rasha Mohammad Obeidat

Proceedings of the 27th International Conference on Computational Linguistics, 2018

Dependent Gated Reading for Cloze-Style Question Answering.

[BibT_eX]

[DOI]

Proceedings of the 27th International Conference on Computational Linguistics, 2018

Training Deep Reactive Policies for Probabilistic Planning Problems.

[BibT_eX]

[DOI]

Murugeswari Issakkimuthu

Proceedings of the Twenty-Eighth International Conference on Automated Planning and Scheduling, 2018

2017

Average-Reward Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Model-Based Reinforcement Learning.

[BibT_eX]

[DOI]

Soumya Ray

Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Adaptive Submodularity with Varying Query Sets: An Application to Active Multi-label Learning.

[BibT_eX]

[DOI]

Robby Goetschalckx

Mandana Hamidi-Haines

Proceedings of the International Conference on Algorithmic Learning Theory, 2017

Multi-Task Structured Prediction for Entity Analysis: Search-Based Learning Algorithms.

[BibT_eX]

[DOI]

Proceedings of The 9th Asian Conference on Machine Learning, 2017

Hindsight Optimization for Hybrid State and Action MDPs.

[BibT_eX]

[DOI]

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Cross Lingual Mention and Entity Embeddings for Cross-Lingual Entity Disambiguation.

[BibT_eX]

[DOI]

Proceedings of the 2016 Text Analysis Conference, 2016

Label Embedding Approach for Transfer Learning.

[BibT_eX]

[DOI]

Rasha Obeidat

Proceedings of the Joint International Conference on Biological Ontology and BioCreative, 2016

Event Nugget Detection with Forward-Backward Recurrent Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

2015

Memory-Effcient Symbolic Online Planning for Factored MDPs.

[BibT_eX]

[DOI]

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Active Imitation Learning of Hierarchical Policies.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Multitask Coactive Learning.

[BibT_eX]

[DOI]

Robby Goetschalckx

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Hindsight Optimization for Probabilistic Planning with Factored Actions.

[BibT_eX]

[DOI]

Murugeswari Issakkimuthu

Proceedings of the Twenty-Fifth International Conference on Automated Planning and Scheduling, 2015

Learning Greedy Policies for the Easy-First Framework.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Factored MCTS for Large Scale Stochastic Planning.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Using trajectory data to improve bayesian optimization for reinforcement learning.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2014

Active lmitation learning: formal and practical reductions to I.I.D. learning.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2014

Structured prediction via output space search.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2014

A Decision-Theoretic Model of Assistance.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2014

HC-Search: A Learning Framework for Search-based Structured Prediction.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2014

Prune-and-Score: Learning for Greedy Coreference Resolution.

[BibT_eX]

[DOI]

Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, 2014

Learning Scripts as Hidden Markov Models.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

Imitation Learning with Demonstrations and Shaping Rewards.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

Coactive Learning for Locally Optimal Problem Solving.

[BibT_eX]

[DOI]

Robby Goetschalckx

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

HC-Search for Multi-Label Prediction: An Empirical Study.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013

Solving Relational MDPs with Exogenous Events and Additive Rewards.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Symbolic Opportunistic Policy Iteration for Factored-Action MDPs.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the Inductive Logic Programming - 23rd International Conference, 2013

Relational Markov Decision Processes: Promise and Prospects.

[BibT_eX]

[DOI]

Proceedings of the Statistical Relational Artificial Intelligence, 2013

HC-Search: Learning Heuristics and Cost Functions for Structured Prediction.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013

2012

An Ensemble Architecture for Learning Complex Problem-Solving Techniques from Demonstration.

[BibT_eX]

[DOI]

ACM Trans. Intell. Syst. Technol., 2012

A relational hierarchical model for decision-theoretic assistance.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2012

Transfer Learning in Sequential Decision Problems: A Hierarchical Bayesian Approach.

[BibT_eX]

[DOI]

Proceedings of the Unsupervised and Transfer Learning, 2012

Accelarating Imitation Learning in Relational Domains via Transfer by Initialization.

[BibT_eX]

[DOI]

Proceedings of the 2nd International Workshop on Statistical Relational AI (StaRAI-12), 2012

A Bayesian Approach for Policy Learning from Trajectory Preference Queries.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the 29th International Conference on Machine Learning, 2012

Planning in Factored Action Spaces with Symbolic Dynamic Programming.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011

The first learning track of the international planning competition.

[BibT_eX]

[DOI]

Roni Khardon

Mach. Learn., 2011

Learning Rules from Incomplete Examples via Implicit Mention Models.

[BibT_eX]

[DOI]

Shahed Sorower

Mohammad NasrEsfahani

Proceedings of the 3rd Asian Conference on Machine Learning, 2011

Automatic Discovery and Transfer of Task Hierarchies in Reinforcement Learning.

[BibT_eX]

[DOI]

AI Mag., 2011

Inverting Grice's Maxims to Learn Rules from Natural Language Extractions.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Neville Mehta

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.

[BibT_eX]

[DOI]

Proceedings of the IJCAI 2011, 2011

2010

Average-Reward Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Encyclopedia of Machine Learning, 2010

Model-Based Reinforcement Learning.

[BibT_eX]

[DOI]

Soumya Ray

Proceedings of the Encyclopedia of Machine Learning, 2010

Incorporating Domain Models into Bayesian Optimization for RL.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Learning Algorithms for Link Prediction Based on Chance Constraints.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Multi-Agent Inverse Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

Bayesian role discovery for multi-agent reinforcement learning.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), 2010

Bayesian Policy Search for Multi-Agent Role Discovery.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models.

[BibT_eX]

[DOI]

Proceedings of the Statistical Relational Artificial Intelligence, 2010

A Computational Decision Theory for Interactive Assistants.

[BibT_eX]

[DOI]

Proceedings of the Interactive Decision Theory and Game Theory, 2010

2009

Guest editorial: special issue on structured prediction.

[BibT_eX]

[DOI]

Charles Parker

Yasemin Altun

Mach. Learn., 2009

Transfer Learning via Relational Templates.

[BibT_eX]

[DOI]

Proceedings of the Inductive Logic Programming, 19th International Conference, 2009

Multiagent Transfer Learning via Assignment-Based Decomposition.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning and Applications, 2009

Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning and Applications, 2009

An Ensemble Learning and Problem Solving Architecture for Airspace Management.

[BibT_eX]

[DOI]

Proceedings of the Twenty-First Conference on Innovative Applications of Artificial Intelligence, 2009

Simulation-based Optimization of Resource Placement and Emergency Response.

[BibT_eX]

[DOI]

Proceedings of the Twenty-First Conference on Innovative Applications of Artificial Intelligence, 2009

Solving multiagent assignment Markov decision processes.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2009), 2009

Lower Bounding Klondike Solitaire with Monte-Carlo Planning.

[BibT_eX]

[DOI]

Ronald Bjarnason

Proceedings of the 19th International Conference on Automated Planning and Scheduling, 2009

2008

Transfer in variable-reward hierarchical reinforcement learning.

[BibT_eX]

[DOI]

Mach. Learn., 2008

Structured machine learning: the next ten years.

[BibT_eX]

[DOI]

Mach. Learn., 2008

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

[BibT_eX]

[DOI]

Hendrik Blockeel

Jude W. Shavlik

Mach. Learn., 2008

Learning to Solve Problems from Exercises.

[BibT_eX]

[DOI]

Comput. Intell., 2008

Learning first-order probabilistic models with combining rules.

[BibT_eX]

[DOI]

Ann. Math. Artif. Intell., 2008

Logical Hierarchical Hidden Markov Models for Modeling User Activities.

[BibT_eX]

[DOI]

Proceedings of the Inductive Logic Programming, 18th International Conference, 2008

Automatic discovery and transfer of MAXQ hierarchies.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2008

2007

Searching Solitaire in Real Time.

[BibT_eX]

Ronald Bjarnason

J. Int. Comput. Games Assoc., 2007

Multi-task reinforcement learning: a hierarchical Bayesian approach.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2007

Learning for efficient retrieval of structured data with noisy queries.

[BibT_eX]

[DOI]

Charles Parker

Proceedings of the Machine Learning, 2007

Exploiting prior knowledge in Intelligent Assistants - Combining relational models with hierarchies.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the Interaction Challenges for Intelligent Assistants, 2007

2006

Scaling Model-Based Average-Reward Reinforcement Learning for Product Delivery.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning: ECML 2006, 2006

Gradient Boosting for Sequence Alignment.

[BibT_eX]

[DOI]

Charles Parker

Proceedings of the Proceedings, 2006

2005

Learning first-order probabilistic models with combining rules.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2005

Dynamic preferences in multi-criteria reinforcement learning.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2005

2002

Model-based Hierarchical Average-reward Reinforcement Learning.

[BibT_eX]

Sandeep Seri

Proceedings of the Machine Learning, 2002

Learning Decision Rules by Randomized Iterative Local Search.

[BibT_eX]

Michael Chisholm

Proceedings of the Machine Learning, 2002

2001

On Exact Learning of Unordered Tree Patterns.

[BibT_eX]

[DOI]

Thomas R. Amoth

Paul Cull

Mach. Learn., 2001

1999

Learning Horn Definitions: Theory and an Application to Planning.

[BibT_eX]

[DOI]

New Gener. Comput., 1999

Exact Learning of Unordered Tree Patterns from Queries.

[BibT_eX]

[DOI]

Thomas R. Amoth

Paul Cull

Proceedings of the Twelfth Annual Conference on Computational Learning Theory, 1999

1998

Learning from Examples and Membership Queries with Structured Determinations.

[BibT_eX]

[DOI]

Stuart Russell

Mach. Learn., 1998

Model-Based Average Reward Reinforcement Learning.

[BibT_eX]

[DOI]

DoKyeong Ok

Artif. Intell., 1998

Learning First-Order Acyclic Horn Programs from Entailment.

[BibT_eX]

Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998

Exact Learning of Tree Patterns from Queries and Counterexamples.

[BibT_eX]

[DOI]

Thomas R. Amoth

Paul Cull

Proceedings of the Eleventh Annual Conference on Computational Learning Theory, 1998

1997

Learning Horn Definitions with Equivalence and Membership Queries.

[BibT_eX]

[DOI]

Proceedings of the Inductive Logic Programming, 7th International Workshop, 1997

Hierarchical Explanation-Based Reinforcement Learning.

[BibT_eX]

Thomas G. Dietterich

Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997

Learning Goal-Decomposition Rules using Exercises.

[BibT_eX]

Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997

Active Learning with Committees.

[BibT_eX]

[DOI]

Ray Liere

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.

[BibT_eX]

[DOI]

Ray Liere

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.

[BibT_eX]

[DOI]

Balas K. Natarajan

J. Artif. Intell. Res., 1996

Scaling Up Average Reward Reinforcement Learning by Approximating the Domain Models and the Value Function.

[BibT_eX]

DoKyeong Ok

Proceedings of the Machine Learning, 1996

Theory-guided Empirical Speedup Learning of Goal Decomposition Rules.

[BibT_eX]

Silvana Roncagliolo

Proceedings of the Machine Learning, 1996

Auto-Exploratory Average Reward Reinforcement Learning.

[BibT_eX]

[DOI]

DoKyeong Ok

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.

[BibT_eX]

[DOI]

Sridhar Mahadevan