← Authors

Brendan Juba

28 papers · 2013–2026 · 9 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (9) πŸƒ Academic Marathon (12) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (10) 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🐝 Cross-Pollinator (8) 🐺 Lone Wolf (3) πŸ† Grand Slam πŸ† Keyword Champion (2) πŸ”₯ Unstoppable (7) ❓ The Questioner πŸ’Ž Century Club (27) πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (134) ⚑ Prolific Year (6)

Conferences

AAAI (10) IJCAI (6) AISTATS (5) ICLR (2) ALT (1) COLT (1) ICML (1) JMLR (1) NIPS (1)

Top co-authors

Roni Stern (5) Hai S. Le (3) Sanmay Das (3) Elena Grigorescu (2) Ning Xie (2) Kuldeep S. Meel (2) Vaishak Belle (2) Karl Wimmer (2) Andrew Estornell (2) Yevgeniy Vorobeychik (2)

Keywords

polynomial time algorithm (3) conditional linear regression (3) first-order logic (3) safe planning (3) action model (2) pac learning (2) model learning (2) implicit learning (2) sum-of-squares logic (2) determinantal point process (2) probabilistic inference (2) pac semantics (2) action model learning (2) approximation algorithm (2) skolem function (2) model-based diagnosis (1) relational learning (1) sample complexity (1) robust statistics (1) density estimation (1)

Papers

The Limitations and Power of NP-Oracle Based Functional Synthesis Techniques AAAI 2026
Polynomial-Time Relational Probabilistic Inference in Open Universes IJCAI 2025
Distribution-Specific Agnostic Conditional Classification With Halfspaces ICLR 2025
An Approximate Skolem Function Counter AAAI 2024
Learning Safe Action Models with Partial Observability AAAI 2024
The Impact of Features Used by Algorithms on Perceptions of Fairness IJCAI 2024
Popularizing Fairness: Group Fairness and Individual Welfare AAAI 2023
Learning Safe Numeric Action Models AAAI 2023
Polynomial Time Reinforcement Learning in Factored State MDPs with Linear Value Functions AISTATS 2022
Learning Probably Approximately Complete and Safe Action Models for Stochastic Worlds AAAI 2022
Conditional Linear Regression for Heterogeneous Covariances AISTATS 2022
Hardness of Maximum Likelihood Learning of DPPs COLT 2022
One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks ICLR 2021
List Learning with Attribute Noise AISTATS 2021
Learning Implicitly with Noisy Data in Linear Arithmetic IJCAI 2021
Probabilistic Generating Circuits ICML 2021
Conditional Linear Regression AISTATS 2020
More Accurate Learning of k-DNF Reference Classes AAAI 2020
Safe Partial Diagnosis from Normal Observations AAAI 2019
Hardness of Improper One-Sided Learning of Conjunctions For All Uniformly Falsifiable CSPs ALT 2019
Implicitly learning to reason in first-order logic NIPS 2019
Polynomial-Time Probabilistic Reasoning with Partial Observations via Implicit Learning in Probability Logics AAAI 2019
Precision-Recall versus Accuracy and the Role of Large Data Sets AAAI 2019
Conditional Sparse $L_p$-norm Regression With Optimal Probability AISTATS 2019
Coordinated Versus Decentralized Exploration In Multi-Agent Multi-Armed Bandits IJCAI 2017
Efficient, Safe, and Probably Approximately Complete Learning of Action Models IJCAI 2017
Integrated Common Sense Learning and Planning in POMDPs JMLR 2016
Implicit Learning of Common Sense for Reasoning IJCAI 2013