Brendan Juba

Orcid: 0000-0001-6542-833X

Affiliations:
  • Washington University in St. Louis, USA


According to our database1, Brendan Juba authored at least 73 papers between 2006 and 2024.

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Bibliography

2024
Learning Linear Utility Functions From Pairwise Comparison Queries.
CoRR, 2024

Safe Learning of PDDL Domains with Conditional Effects - Extended Version.
CoRR, 2024

Polynomial time auditing of statistical subgroup fairness for Gaussian data.
CoRR, 2024

The Impact of Features Used by Algorithms on Perceptions of Fairness.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Safe Learning of PDDL Domains with Conditional Effects.
Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling, 2024

Distribution-Specific Auditing for Subgroup Fairness.
Proceedings of the 5th Symposium on Foundations of Responsible Computing, 2024

An Approximate Skolem Function Counter.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Learning Safe Action Models with Partial Observability.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Learnability with PAC Semantics for Multi-agent Beliefs.
Theory Pract. Log. Program., July, 2023

The (Un)Scalability of Informed Heuristic Function Estimation in NP-Hard Search Problems.
Trans. Mach. Learn. Res., 2023

Enhancing Numeric-SAM for Learning with Few Observations.
CoRR, 2023

Learning Safe Numeric Action Models.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Popularizing Fairness: Group Fairness and Individual Welfare.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Hardness of Maximum Likelihood Learning of DPPs.
Electron. Colloquium Comput. Complex., 2022

An Example of the SAM+ Algorithm for Learning Action Models for Stochastic Worlds.
CoRR, 2022

A Scalable Shannon Entropy Estimator.
Proceedings of the Computer Aided Verification - 34th International Conference, 2022

Conditional Linear Regression for Heterogeneous Covariances.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Polynomial Time Reinforcement Learning in Factored State MDPs with Linear Value Functions.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Learning Probably Approximately Complete and Safe Action Models for Stochastic Worlds.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Safe Multi-Agent Pathfinding with Time Uncertainty.
J. Artif. Intell. Res., 2021

Provable Hierarchical Lifelong Learning with a Sketch-based Modular Architecture.
CoRR, 2021

Polynomial Time Reinforcement Learning in Correlated FMDPs with Linear Value Functions.
CoRR, 2021

Safe Learning of Lifted Action Models.
Proceedings of the 18th International Conference on Principles of Knowledge Representation and Reasoning, 2021

Learning Implicitly with Noisy Data in Linear Arithmetic.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Probabilistic Generating Circuits.
Proceedings of the 38th International Conference on Machine Learning, 2021

One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks.
Proceedings of the 9th International Conference on Learning Representations, 2021

List Learning with Attribute Noise.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
A Tensor Decomposition Method for Unsupervised Feature Learning on Satellite Imagery.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020

Polynomial-Time Implicit Learnability in SMT.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

Conditional Linear Regression.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

More Accurate Learning of k-DNF Reference Classes.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
The Price of Uncertain Priors in Source Coding.
IEEE Trans. Inf. Theory, 2019

Query-driven PAC-Learning for Reasoning.
CoRR, 2019

Implicitly learning to reason in first-order logic.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Conditional Sparse $L_p$-norm Regression With Optimal Probability.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Safe Partial Diagnosis from Normal Observations.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Precision-Recall versus Accuracy and the Role of Large Data Sets.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Polynomial-Time Probabilistic Reasoning with Partial Observations via Implicit Learning in Probability Logics.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
AC<sup>0</sup>∘MOD<sub>2</sub> lower bounds for the Boolean Inner Product.
J. Comput. Syst. Sci., 2018

Hardness of improper one-sided learning of conjunctions for all uniformly falsifiable CSPs.
Electron. Colloquium Comput. Complex., 2018

Conditional Sparse 𝓁<sub>p</sub>-norm Regression With Optimal Probability.
CoRR, 2018

Anomaly Explanation Using Metadata.
Proceedings of the 2018 IEEE Winter Conference on Applications of Computer Vision, 2018

Learning Abduction Using Partial Observability.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Conditional Linear Regression.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Conditional Sparse Linear Regression.
Proceedings of the 8th Innovations in Theoretical Computer Science Conference, 2017

Efficient, Safe, and Probably Approximately Complete Learning of Action Models.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Coordinated Versus Decentralized Exploration In Multi-Agent Multi-Armed Bandits.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Learning Abduction under Partial Observability.
Proceedings of the 6th Workshop on Automated Knowledge Base Construction, 2017

An Improved Algorithm for Learning to Perform Exception-Tolerant Abduction.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Integrated Common Sense Learning and Planning in POMDPs.
J. Mach. Learn. Res., 2016

AC^0 o MOD_2 Lower Bounds for the Boolean Inner Product.
Proceedings of the 43rd International Colloquium on Automata, Languages, and Programming, 2016

Learning Abductive Reasoning Using Random Examples.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
AC<sup>0</sup> \circ MOD<sub>2</sub> lower bounds for the Boolean Inner Product.
Electron. Colloquium Comput. Complex., 2015

Principled Sampling for Anomaly Detection.
Proceedings of the 22nd Annual Network and Distributed System Security Symposium, 2015

Restricted Distribution Automatizability in PAC-Semantics.
Proceedings of the 2015 Conference on Innovations in Theoretical Computer Science, 2015

The price of uncertainty in communication.
Proceedings of the 53rd Annual Allerton Conference on Communication, 2015

2013
On Non-automatizability in PAC-Semantics.
Electron. Colloquium Comput. Complex., 2013

PAC Quasi-automatizability of Resolution over Restricted Distributions
CoRR, 2013

Compatibility among diversity Foundations, lessons, and directions of semantic communication.
Proceedings of the 2013 IEEE International Conference on Pervasive Computing and Communications Workshops, 2013

Implicit Learning of Common Sense for Reasoning.
Proceedings of the IJCAI 2013, 2013

2012
On learning finite-state quantum sources.
Quantum Inf. Comput., 2012

Massive Online Teaching to Bounded Learners.
Electron. Colloquium Comput. Complex., 2012

Learning implicitly in reasoning in PAC-Semantics
CoRR, 2012

2011
Reliable end-user communication under a changing packet network protocol.
Proceedings of the 30th Annual ACM Symposium on Principles of Distributed Computing, 2011

Compression without a common prior: an information-theoretic justification for ambiguity in language.
Proceedings of the Innovations in Computer Science, 2011

Semantic Communication for Simple Goals Is Equivalent to On-line Learning.
Proceedings of the Algorithmic Learning Theory - 22nd International Conference, 2011

Universal Semantic Communication.
Springer, ISBN: 978-3-642-23296-1, 2011

2010
Universal semantic communication.
PhD thesis, 2010

Efficient Semantic Communication via Compatible Beliefs.
Electron. Colloquium Comput. Complex., 2010

2009
A Theory of Goal-Oriented Communication.
Electron. Colloquium Comput. Complex., 2009

2008
Universal Semantic Communication II: A Theory of Goal-Oriented Communication.
Electron. Colloquium Comput. Complex., 2008

2007
Universal Semantic Communication I.
Electron. Colloquium Comput. Complex., 2007

2006
Estimating relatedness via data compression.
Proceedings of the Machine Learning, 2006


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