Brendan Juba

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 71

Top Topics

Linear Regression

Partial Observability

Top Venues

Electron. Colloquium Comput. Complex.

Publications

Argaman Mordoch, Enrico Scala, Roni Stern, Brendan Juba
Safe Learning of PDDL Domains with Conditional Effects. ICAPS (2024)
Daniel Hsu, Jizhou Huang, Brendan Juba
Distribution-Specific Auditing for Subgroup Fairness. FORC (2024)
Hai S. Le, Brendan Juba, Roni Stern
Learning Safe Action Models with Partial Observability. AAAI (2024)
Luise Ge, Brendan Juba, Yevgeniy Vorobeychik
Learning Linear Utility Functions From Pairwise Comparison Queries. CoRR (2024)
Daniel Hsu, Jizhou Huang, Brendan Juba
Polynomial time auditing of statistical subgroup fairness for Gaussian data. CoRR (2024)
Arijit Shaw, Brendan Juba, Kuldeep S. Meel
An Approximate Skolem Function Counter. AAAI (2024)
Argaman Mordoch, Enrico Scala, Roni Stern, Brendan Juba
Safe Learning of PDDL Domains with Conditional Effects - Extended Version. CoRR (2024)
Argaman Mordoch, Shahaf S. Shperberg, Roni Stern, Brendan Juba
Enhancing Numeric-SAM for Learning with Few Observations. CoRR (2023)
Ionela G. Mocanu, Vaishak Belle, Brendan Juba
Learnability with PAC Semantics for Multi-agent Beliefs. Theory Pract. Log. Program. 23 (4) (2023)
Andrew Estornell, Sanmay Das, Brendan Juba, Yevgeniy Vorobeychik
Popularizing Fairness: Group Fairness and Individual Welfare. AAAI (2023)
Ionela Georgiana Mocanu, Vaishak Belle, Brendan Juba
Learnability with PAC Semantics for Multi-agent Beliefs. CoRR (2023)
Argaman Mordoch, Brendan Juba, Roni Stern
Learning Safe Numeric Action Models. AAAI (2023)
Ionela Georgiana Mocanu, Vaishak Belle, Brendan Juba
Learnability with PAC Semantics for Multi-agent Beliefs. AAMAS (2023)
Arijit Shaw, Brendan Juba, Kuldeep S. Meel
An Approximate Skolem Function Counter. CoRR (2023)
Sumedh Pendurkar, Taoan Huang, Brendan Juba, Jiapeng Zhang, Sven Koenig, Guni Sharon
The (Un)Scalability of Informed Heuristic Function Estimation in NP-Hard Search Problems. Trans. Mach. Learn. Res. 2023 (2023)
Brendan Juba, Roni Stern
Learning Probably Approximately Complete and Safe Action Models for Stochastic Worlds. AAAI (2022)
Brendan Juba, Roni Stern
An Example of the SAM+ Algorithm for Learning Action Models for Stochastic Worlds. CoRR (2022)
Priyanka Golia, Brendan Juba, Kuldeep S. Meel
A Scalable Shannon Entropy Estimator. CAV (1) (2022)
Leda Liang, Brendan Juba
Conditional Linear Regression for Heterogeneous Covariances. AISTATS (2022)
Priyanka Golia, Brendan Juba, Kuldeep S. Meel
A Scalable Shannon Entropy Estimator. CoRR (2022)
Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie
Hardness of Maximum Likelihood Learning of DPPs. COLT (2022)
Zihao Deng, Siddartha Devic, Brendan Juba
Polynomial Time Reinforcement Learning in Factored State MDPs with Linear Value Functions. AISTATS (2022)
Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie
Hardness of Maximum Likelihood Learning of DPPs. CoRR (2022)
Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie
Hardness of Maximum Likelihood Learning of DPPs. Electron. Colloquium Comput. Complex. (2022)
Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan, Xin Wang, Qiuyi Zhang
One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks. CoRR (2021)
Honghua Zhang, Brendan Juba, Guy Van den Broeck
Probabilistic Generating Circuits. ICML (2021)
Tomer Shahar, Shashank Shekhar, Dor Atzmon, Abdallah Saffidine, Brendan Juba, Roni Stern
Safe Multi-Agent Pathfinding with Time Uncertainty. J. Artif. Intell. Res. 70 (2021)
Mahdi Cheraghchi, Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie
List Learning with Attribute Noise. AISTATS (2021)
Brendan Juba, Hai S. Le, Roni Stern
Safe Learning of Lifted Action Models. CoRR (2021)
Siddartha Devic, Zihao Deng, Brendan Juba
Polynomial Time Reinforcement Learning in Correlated FMDPs with Linear Value Functions. CoRR (2021)
Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan, Xin Wang, Qiuyi Zhang
One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks. ICLR (2021)
Brendan Juba, Leda Liang
Conditional Linear Regression for Heterogeneous Covariances. CoRR (2021)
Alexander Philipp Rader, Ionela G. Mocanu, Vaishak Belle, Brendan Juba
Learning Implicitly with Noisy Data in Linear Arithmetic. IJCAI (2021)
Brendan Juba, Hai S. Le, Roni Stern
Safe Learning of Lifted Action Models. KR (2021)
Honghua Zhang, Brendan Juba, Guy Van den Broeck
Probabilistic Generating Circuits. CoRR (2021)
Zihao Deng, Zee Fryer, Brendan Juba, Rina Panigrahy, Xin Wang
Provable Hierarchical Lifelong Learning with a Sketch-based Modular Architecture. CoRR (2021)
Golnoosh Dehghanpoor, Michael Frachetti, Brendan Juba
A Tensor Decomposition Method for Unsupervised Feature Learning on Satellite Imagery. IGARSS (2020)
Ionela G. Mocanu, Vaishak Belle, Brendan Juba
Polynomial-Time Implicit Learnability in SMT. ECAI (2020)
Mahdi Cheraghchi, Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie
List Learning with Attribute Noise. CoRR (2020)
Diego Calderon, Brendan Juba, Sirui Li, Zongyi Li, Lisa Ruan
Conditional Linear Regression. AISTATS (2020)
Brendan Juba, Hengxuan Li
More Accurate Learning of k-DNF Reference Classes. AAAI (2020)
Alexander Philipp Rader, Ionela G. Mocanu, Vaishak Belle, Brendan Juba
Learning Implicitly with Noisy Data in Linear Arithmetic. CoRR (2020)
Alexander Durgin, Brendan Juba
Hardness of Improper One-Sided Learning of Conjunctions For All Uniformly Falsifiable CSPs. ALT (2019)
Vaishak Belle, Brendan Juba
Implicitly learning to reason in first-order logic. NeurIPS (2019)
John Hainline, Brendan Juba, Hai S. Le, David P. Woodruff
Conditional Sparse $L_p$-norm Regression With Optimal Probability. AISTATS (2019)
Brendan Juba, Hai S. Le
Precision-Recall versus Accuracy and the Role of Large Data Sets. AAAI (2019)
Mark Braverman, Brendan Juba
The Price of Uncertain Priors in Source Coding. IEEE Trans. Inf. Theory 65 (2) (2019)
Roni Stern, Brendan Juba
Safe Partial Diagnosis from Normal Observations. AAAI (2019)
Brendan Juba
Query-driven PAC-Learning for Reasoning. CoRR (2019)
Brendan Juba
Polynomial-Time Probabilistic Reasoning with Partial Observations via Implicit Learning in Probability Logics. AAAI (2019)
Vaishak Belle, Brendan Juba
Implicitly Learning to Reason in First-Order Logic. CoRR (2019)
Mahdi Cheraghchi, Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie
lower bounds for the Boolean Inner Product. J. Comput. Syst. Sci. 97 (2018)
Brendan Juba, Zongyi Li, Evan Miller
Learning Abduction Under Partial Observability. AAAI (2018)
Alexander Durgin, Brendan Juba
Hardness of improper one-sided learning of conjunctions for all uniformly falsifiable CSPs. Electron. Colloquium Comput. Complex. 25 (2018)
Brendan Juba, Zongyi Li, Evan Miller
Learning Abduction Using Partial Observability. AAAI (2018)
Diego Calderon, Brendan Juba, Sirui Li, Zongyi Li, Lisa Ruan
Conditional Linear Regression. CoRR (2018)
Diego Calderon, Brendan Juba, Zongyi Li, Lisa Ruan
Conditional Linear Regression. AAAI (2018)
Di Qi, Joshua Arfin, Mengxue Zhang, Tushar Mathew, Robert Pless, Brendan Juba
Anomaly Explanation Using Metadata. WACV (2018)
John Hainline, Brendan Juba, Hai S. Le, David P. Woodruff
-norm Regression With Optimal Probability. CoRR (2018)
Mark Braverman, Brendan Juba
The Price of Uncertain Priors in Source Coding. CoRR (2018)
Brendan Juba
Polynomial-time probabilistic reasoning with partial observations via implicit learning in probability logics. CoRR (2018)
Roni Stern, Brendan Juba
Efficient, Safe, and Probably Approximately Complete Learning of Action Models. IJCAI (2017)
Brendan Juba, Zongyi Li, Evan Miller
Learning Abduction under Partial Observability. CoRR (2017)
Roni Stern, Brendan Juba
Efficient, Safe, and Probably Approximately Complete Learning of Action Models. CoRR (2017)
Brendan Juba
Conditional Sparse Linear Regression. ITCS (2017)
Mithun Chakraborty, Kai Yee Phoebe Chua, Sanmay Das, Brendan Juba
Coordinated Versus Decentralized Exploration In Multi-Agent Multi-Armed Bandits. IJCAI (2017)
Zongyi Li, Brendan Juba, Evan Miller
Learning Abduction under Partial Observability. AKBC@NIPS (2017)
Brendan Juba
Integrated Common Sense Learning and Planning in POMDPs. J. Mach. Learn. Res. 17 (2016)
Brendan Juba
Learning Abductive Reasoning Using Random Examples. AAAI (2016)
Mahdi Cheraghchi, Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie
AC^0 o MOD_2 Lower Bounds for the Boolean Inner Product. ICALP (2016)
Brendan Juba
Conditional Sparse Linear Regression. CoRR (2016)
Brendan Juba
Restricted Distribution Automatizability in PAC-Semantics. ITCS (2015)
Mark Braverman, Brendan Juba
The price of uncertainty in communication. Allerton (2015)
Mahdi Cheraghchi, Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie
lower bounds for the Boolean Inner Product. Electron. Colloquium Comput. Complex. 22 (2015)
Brendan Juba, Christopher Musco, Fan Long, Stelios Sidiroglou-Douskos, Martin C. Rinard
Principled Sampling for Anomaly Detection. NDSS (2015)
Brendan Juba, Ryan Williams
Massive online teaching to bounded learners. ITCS (2013)
Brendan Juba
On Non-automatizability in PAC-Semantics. Electron. Colloquium Comput. Complex. 20 (2013)
Brendan Juba
PAC Quasi-automatizability of Resolution over Restricted Distributions CoRR (2013)
Brendan Juba
Compatibility among diversity Foundations, lessons, and directions of semantic communication. PerCom Workshops (2013)
Brendan Juba
Implicit Learning of Common Sense for Reasoning. IJCAI (2013)
Brendan Juba
On learning finite-state quantum sources. Quantum Inf. Comput. 12 (1-2) (2012)
Brendan Juba
Learning implicitly in reasoning in PAC-Semantics CoRR (2012)
Brendan Juba, Ryan Williams
Massive Online Teaching to Bounded Learners. Electron. Colloquium Comput. Complex. 19 (2012)
Oded Goldreich, Brendan Juba, Madhu Sudan
A theory of goal-oriented communication. J. ACM 59 (2) (2012)
Brendan Juba, Santosh S. Vempala
Semantic Communication for Simple Goals Is Equivalent to On-line Learning. ALT (2011)
Brendan Juba, Madhu Sudan
Efficient Semantic Communication via Compatible Beliefs. ICS (2011)
Brendan Juba
Reliable end-user communication under a changing packet network protocol. PODC (2011)
Oded Goldreich, Brendan Juba, Madhu Sudan
A theory of goal-oriented communication. PODC (2011)
Brendan Juba, Adam Tauman Kalai, Sanjeev Khanna, Madhu Sudan
Compression without a common prior: an information-theoretic justification for ambiguity in language. ICS (2011)
Brendan Juba, Madhu Sudan
Efficient Semantic Communication via Compatible Beliefs. Electron. Colloquium Comput. Complex. 17 (2010)
Oded Goldreich, Brendan Juba, Madhu Sudan
A Theory of Goal-Oriented Communication. Electron. Colloquium Comput. Complex. 16 (2009)
Brendan Juba
On Learning Finite-State Quantum Sources CoRR (2009)
Brendan Juba, Madhu Sudan
Universal semantic communication I. STOC (2008)
Brendan Juba, Madhu Sudan
Universal Semantic Communication II: A Theory of Goal-Oriented Communication. Electron. Colloquium Comput. Complex. 15 (095) (2008)
Brendan Juba, Madhu Sudan
Universal Semantic Communication I. Electron. Colloquium Comput. Complex. 14 (084) (2007)
Brendan Juba
Estimating relatedness via data compression. ICML (2006)