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← Authors

Brendan Juba

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

Achievements

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+12 more ↓ 🌍 Conference Polyglot (9) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (10) πŸƒ Academic Marathon (12)
🐣 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