引用次数
引用: 1,075
H-指数: 18
I10-指数 : 27
出版物: 75
An Improved Algorithm for Learning to Perform Exception-Tolerant Abduction.
Mengxue Zhang , Tushar Mathew , Brendan A Juba
AAAI 1257 -1265
11
2017
Universal Semantic Communication I.
Madhu Sudan , Brendan Juba
Electronic Colloquium on Computational Complexity 14
55
2007
Universal Semantic Communication II: A Theory of Goal-Oriented Communication
Madhu Sudan , Brendan Juba
Electronic Colloquium on Computational Complexity 15
12
2008
On Non-automatizability in PAC-Semantics.
Brendan Juba
Electronic Colloquium on Computational Complexity 20 94
1
2013
Learning abductive reasoning using random examples
Brendan Juba
national conference on artificial intelligence 999 -1007
12
2016
Integrated common sense learning and planning in POMDPs
Brendan Juba
Journal of Machine Learning Research 17 ( 1) 3276 -3312
8
2016
Hardness of Improper One-Sided Learning of Conjunctions For All Uniformly Falsifiable CSPs
Brendan Juba , Alexander Durgin
algorithmic learning theory 369 -382
1
2019
On learning finite-state quantum sources
Brendan Juba
Quantum Information & Computation 12 ( 1) 105 -118
2012
Conditional Sparse L_p-norm Regression With Optimal Probability
Brendan Juba , David P. Woodruff , John Hainline , Hai S. Le
international conference on artificial intelligence and statistics 1042 -1050
2019
Implicitly Learning to Reason in First-Order Logic
Brendan Juba , Vaishak Belle
neural information processing systems 32 3376 -3386
4
2019
Polynomial-Time Implicit Learnability in SMT.
Brendan Juba , Vaishak Belle , Ionela G. Mocanu
european conference on artificial intelligence 1152 -1158
2
2020
A Tensor Decomposition Method for Unsupervised Feature Learning on Satellite Imagery
Michael Frachetti , Brendan Juba , Golnoosh Dehghanpoor
international geoscience and remote sensing symposium 1679 -1682
2020
Safe Multi-Agent Pathfinding with Time Uncertainty
Dor Atzmon , Shashank Shekhar , Tomer Shahar , Abdallah Saffidine
Journal of Artificial Intelligence Research 70 923 -954
9
2021
One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks.
Atish Agarwala , Abhimanyu Das , Brendan Juba , Rina Panigrahy
arXiv: Learning
5
2021
Learning Implicitly with Noisy Data in Linear Arithmetic.
Brendan Juba , Vaishak Belle , Ionela G. Mocanu , Alexander Philipp Rader
4th Knowledge Representation and Reasoning Meets Machine Learning Workshop (KR2ML 2020), at NeurIPS
2
2020
Anomaly Explanation Using Metadata
Di Qi , Joshua Arfin , Mengxue Zhang , Tushar Mathew
workshop on applications of computer vision 1916 -1924
2018
Reliable end-user communication under a changing packet network protocol
Brendan Juba
principles of distributed computing 339 -340
2011
AC0∘MOD2 lower bounds for the Boolean Inner Product
Mahdi Cheraghchi , Elena Grigorescu , Brendan Juba , Karl Wimmer
Journal of Computer and System Sciences 97 45 -59
3
2018
Massive online teaching to bounded learners
Brendan Juba , Ryan Williams
Proceedings of the 4th conference on Innovations in Theoretical Computer Science - ITCS '13 1 -10
4
2013
A theory of goal-oriented communication
Oded Goldreich , Brendan Juba , Madhu Sudan
Journal of the ACM 59 ( 2) 1 -65
67
2012