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Farhad Shakerin
Farhad Shakerin
Senior Software Engineer, Microsoft
在 microsoft.com 的电子邮件经过验证
标题
引用次数
引用次数
年份
Aqua: Asp-based visual question answering
K Basu, F Shakerin, G Gupta
International Symposium on Practical Aspects of Declarative Languages, 57-72, 2020
442020
A new algorithm to automate inductive learning of default theories
F Shakerin, E Salazar, G Gupta
Theory and Practice of Logic Programming 17 (5-6), 1010-1026, 2017
332017
Knowledge-driven natural language understanding of english text and its applications
K Basu, SC Varanasi, F Shakerin, J Arias, G Gupta
Proceedings of the AAAI Conference on Artificial Intelligence 35 (14), 12554 …, 2021
322021
Induction of non-monotonic logic programs to explain boosted tree models using LIME
F Shakerin, G Gupta
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3052-3059, 2019
232019
White-box induction from SVM models: explainable AI with logic programming
F Shakerin, G Gupta
Theory and Practice of Logic Programming 20 (5), 656-670, 2020
162020
FOLD-RM: a scalable, efficient, and explainable inductive learning algorithm for multi-category classification of mixed data
H Wang, F Shakerin, G Gupta
Theory and Practice of Logic Programming 22 (5), 658-677, 2022
142022
Square: Semantics-based question answering and reasoning engine
K Basu, SC Varanasi, F Shakerin, G Gupta
arXiv preprint arXiv:2009.10239, 2020
142020
A case for query-driven predicate answer set programming
G Gupta, E Salazar, K Marple, Z Chen, F Shakerin
EPiC Series in Computing 51, 64-68, 2017
112017
Automating common sense reasoning with ASP and s (CASP)
G Gupta, E Salazar, SC Varanasi, K Basu, J Arias, F Shakerin, R Min, F Li, ...
Proceedings of 2nd Workshop on Goal-directed Execution of Answer Set …, 2022
92022
An asp-based approach to answering natural language questions for texts
D Pendharkar, K Basu, F Shakerin, G Gupta
Theory and Practice of Logic Programming 22 (3), 419-443, 2022
62022
Logic programming-based approaches in explainable AI and natural language processing
F Shakerin
Department of Computer Science, The University of Texas at Dallas. PhD thesis, 2020
52020
Prolog: past, present, and future
G Gupta, E Salazar, F Shakerin, J Arias, SC Varanasi, K Basu, H Wang, ...
Prolog: The Next 50 Years, 48-61, 2023
42023
Logic-based explainable and incremental machine learning
G Gupta, H Wang, K Basu, F Shakerin, E Salazar, SC Varanasi, ...
Prolog: The Next 50 Years, 346-358, 2023
32023
Formalizing Informal Logic and Natural Language Deductivism.
G Gupta, S Varnasi, K Basu, Z Chen, E Salazar, F Shakerin, S Erbatur, ...
ICLP Workshops, 2021
32021
Whitebox induction of default rules using high-utility itemset mining
F Shakerin, G Gupta
International Symposium on Practical Aspects of Declarative Languages, 168-176, 2020
32020
Tutorial: Automating Commonsense Reasoning.
G Gupta, E Salazar, SC Varanasi, K Basu, J Arias, F Shakerin, F Li, ...
ICLP Workshops, 2022
22022
Induction of non-monotonic rules from statistical learning models using high-utility itemset mining
F Shakerin, G Gupta
arXiv preprint arXiv:1905.11226, 2019
22019
Heuristic Based Induction of Answer Set Programs, From Default theories to Combinatorial problems
S Farhad, G Gupta
Up-and-Coming and Short Papers of the 28th International Conference on …, 2018
2*2018
Automating Common Sense Reasoning
G Gupta, E Salazar, SC Varanasi, K Basu, F Shakerin, F Li, H Wang, ...
2
Counterfactual Explanation Generation with s (CASP)
S Dasgupta, F Shakerin, J Arias, E Salazar, G Gupta
arXiv preprint arXiv:2310.14497, 2023
12023
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