Brendan Juba

According to our database, Brendan Juba authored at least 68 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

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

Argaman Mordoch, Enrico Scala, Roni Stern, Brendan Juba

CoRR, 2024

Polynomial time auditing of statistical subgroup fairness for Gaussian data.

Daniel Hsu, Jizhou Huang, Brendan Juba

CoRR, 2024

An Approximate Skolem Function Counter.

Arijit Shaw, Brendan Juba, Kuldeep S. Meel

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Learning Safe Action Models with Partial Observability.

Hai S. Le, Brendan Juba, Roni Stern

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Learnability with PAC Semantics for Multi-agent Beliefs.

Ionela Georgiana Mocanu, Vaishak Belle, Brendan Juba

Theory Pract. Log. Program., July, 2023

Enhancing Numeric-SAM for Learning with Few Observations.

Argaman Mordoch, Shahaf S. Shperberg, Roni Stern, Brendan Juba

CoRR, 2023

Learning Safe Numeric Action Models.

Argaman Mordoch, Brendan Juba, Roni Stern

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

Popularizing Fairness: Group Fairness and Individual Welfare.

Andrew Estornell, Sanmay Das, Brendan Juba, Yevgeniy Vorobeychik

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

2022

Hardness of Maximum Likelihood Learning of DPPs.

Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie

Electron. Colloquium Comput. Complex., 2022

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

Brendan Juba, Roni Stern

CoRR, 2022

A Scalable Shannon Entropy Estimator.

Priyanka Golia, Brendan Juba, Kuldeep S. Meel

Proceedings of the Computer Aided Verification - 34th International Conference, 2022

Conditional Linear Regression for Heterogeneous Covariances.

Leda Liang, Brendan Juba

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Polynomial Time Reinforcement Learning in Factored State MDPs with Linear Value Functions.

Zihao Deng, Siddartha Devic, Brendan Juba

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Learning Probably Approximately Complete and Safe Action Models for Stochastic Worlds.

Brendan Juba, Roni Stern

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Safe Multi-Agent Pathfinding with Time Uncertainty.

Tomer Shahar, Shashank Shekhar, Dor Atzmon, Abdallah Saffidine, Brendan Juba, Roni Stern

J. Artif. Intell. Res., 2021

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

Zihao Deng, Zee Fryer, Brendan Juba, Rina Panigrahy, Xin Wang

CoRR, 2021

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

Siddartha Devic, Zihao Deng, Brendan Juba

CoRR, 2021

Safe Learning of Lifted Action Models.

Brendan Juba, Hai S. Le, Roni Stern

Proceedings of the 18th International Conference on Principles of Knowledge Representation and Reasoning, 2021

Learning Implicitly with Noisy Data in Linear Arithmetic.

Alexander Philipp Rader, Ionela Georgiana Mocanu, Vaishak Belle, Brendan Juba

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Probabilistic Generating Circuits.

Honghua Zhang, Brendan Juba, Guy Van den Broeck

Proceedings of the 38th International Conference on Machine Learning, 2021

One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks.

Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan, Xin Wang, Qiuyi Zhang

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

List Learning with Attribute Noise.

Mahdi Cheraghchi, Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

A Tensor Decomposition Method for Unsupervised Feature Learning on Satellite Imagery.

Golnoosh Dehghanpoor, Michael D. Frachetti, Brendan Juba

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020

Polynomial-Time Implicit Learnability in SMT.

Ionela Georgiana Mocanu, Vaishak Belle, Brendan Juba

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.

Diego Calderon, Brendan Juba, Sirui Li, Zongyi Li, Lisa Ruan

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

More Accurate Learning of k-DNF Reference Classes.

Brendan Juba, Hengxuan Li

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

2019

The Price of Uncertain Priors in Source Coding.

Mark Braverman, Brendan Juba

IEEE Trans. Inf. Theory, 2019

Query-driven PAC-Learning for Reasoning.

Brendan Juba

CoRR, 2019

Implicitly learning to reason in first-order logic.

Vaishak Belle, Brendan Juba

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.

John Hainline, Brendan Juba, Hai S. Le, David P. Woodruff

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Safe Partial Diagnosis from Normal Observations.

Roni Stern, Brendan Juba

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Precision-Recall versus Accuracy and the Role of Large Data Sets.

Brendan Juba, Hai S. Le

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Polynomial-Time Probabilistic Reasoning with Partial Observations via Implicit Learning in Probability Logics.

Brendan Juba

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

AC⁰∘MOD₂ lower bounds for the Boolean Inner Product.

Mahdi Cheraghchi, Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie

J. Comput. Syst. Sci., 2018

Hardness of improper one-sided learning of conjunctions for all uniformly falsifiable CSPs.

Alexander Durgin, Brendan Juba

Electron. Colloquium Comput. Complex., 2018

Conditional Sparse 𝓁_p-norm Regression With Optimal Probability.

John Hainline, Brendan Juba, Hai S. Le, David P. Woodruff

CoRR, 2018

Anomaly Explanation Using Metadata.

Di Qi, Joshua Arfin, Mengxue Zhang, Tushar Mathew, Robert Pless, Brendan Juba

Proceedings of the 2018 IEEE Winter Conference on Applications of Computer Vision, 2018

Learning Abduction Using Partial Observability.

Brendan Juba, Zongyi Li, Evan Miller

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Conditional Linear Regression.

Diego Calderon, Brendan Juba, Zongyi Li, Lisa Ruan

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Conditional Sparse Linear Regression.

Brendan Juba

Proceedings of the 8th Innovations in Theoretical Computer Science Conference, 2017

Efficient, Safe, and Probably Approximately Complete Learning of Action Models.

Roni Stern, Brendan Juba

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Coordinated Versus Decentralized Exploration In Multi-Agent Multi-Armed Bandits.

Mithun Chakraborty, Kai Yee Phoebe Chua, Sanmay Das, Brendan Juba

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Learning Abduction under Partial Observability.

Zongyi Li, Brendan Juba, Evan Miller

Proceedings of the 6th Workshop on Automated Knowledge Base Construction, 2017

An Improved Algorithm for Learning to Perform Exception-Tolerant Abduction.

Mengxue Zhang, Tushar Mathew, Brendan A. Juba

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

2016

Integrated Common Sense Learning and Planning in POMDPs.

Brendan Juba

J. Mach. Learn. Res., 2016

AC^0 o MOD_2 Lower Bounds for the Boolean Inner Product.

Mahdi Cheraghchi, Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie

Proceedings of the 43rd International Colloquium on Automata, Languages, and Programming, 2016

Learning Abductive Reasoning Using Random Examples.

Brendan Juba

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

AC⁰ \circ MOD₂ lower bounds for the Boolean Inner Product.

Mahdi Cheraghchi, Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie

Electron. Colloquium Comput. Complex., 2015

Principled Sampling for Anomaly Detection.

Brendan Juba, Christopher Musco, Fan Long, Stelios Sidiroglou-Douskos, Martin C. Rinard

Proceedings of the 22nd Annual Network and Distributed System Security Symposium, 2015

Restricted Distribution Automatizability in PAC-Semantics.

Brendan Juba

Proceedings of the 2015 Conference on Innovations in Theoretical Computer Science, 2015

The price of uncertainty in communication.

Mark Braverman, Brendan Juba

Proceedings of the 53rd Annual Allerton Conference on Communication, 2015

2013

On Non-automatizability in PAC-Semantics.

Brendan Juba

Electron. Colloquium Comput. Complex., 2013

PAC Quasi-automatizability of Resolution over Restricted Distributions

Brendan Juba

CoRR, 2013

Compatibility among diversity Foundations, lessons, and directions of semantic communication.

Brendan Juba

Proceedings of the 2013 IEEE International Conference on Pervasive Computing and Communications Workshops, 2013

Implicit Learning of Common Sense for Reasoning.

Brendan Juba

Proceedings of the IJCAI 2013, 2013

2012

On learning finite-state quantum sources.

Brendan Juba

Quantum Inf. Comput., 2012

A theory of goal-oriented communication.

Oded Goldreich, Brendan Juba, Madhu Sudan

J. ACM, 2012

Massive Online Teaching to Bounded Learners.

Brendan Juba, Ryan Williams

Electron. Colloquium Comput. Complex., 2012

Learning implicitly in reasoning in PAC-Semantics

Brendan Juba

CoRR, 2012

2011

Reliable end-user communication under a changing packet network protocol.

Brendan Juba

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.

Brendan Juba, Adam Tauman Kalai, Sanjeev Khanna, Madhu Sudan

Proceedings of the Innovations in Computer Science, 2011

Semantic Communication for Simple Goals Is Equivalent to On-line Learning.

Brendan Juba, Santosh S. Vempala

Proceedings of the Algorithmic Learning Theory - 22nd International Conference, 2011

Universal Semantic Communication.

Brendan Juba

Springer, ISBN: 978-3-642-23296-1, 2011

2010

Universal semantic communication.

Brendan A. Juba

PhD thesis, 2010

Efficient Semantic Communication via Compatible Beliefs.

Brendan Juba, Madhu Sudan

Electron. Colloquium Comput. Complex., 2010

2008

Universal Semantic Communication II: A Theory of Goal-Oriented Communication.

Brendan Juba, Madhu Sudan

Electron. Colloquium Comput. Complex., 2008

2007

Universal Semantic Communication I.

Brendan Juba, Madhu Sudan

Electron. Colloquium Comput. Complex., 2007

2006

Estimating relatedness via data compression.

Brendan Juba

Proceedings of the Machine Learning, 2006