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Farhad Shakerin
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2020 – today
- 2024
- [c12]Sopam Dasgupta, Farhad Shakerin, Elmer Salazar, Joaquín Arias, Gopal Gupta:
Causally Constrained Counterfactual Generation using ASP. ICLP Workshops 2024 - [i11]Sopam Dasgupta, Farhad Shakerin, Joaquín Arias, Elmer Salazar, Gopal Gupta:
Counterfactual Generation with Answer Set Programming. CoRR abs/2402.04382 (2024) - 2023
- [p2]Gopal Gupta, Elmer Salazar, Farhad Shakerin, Joaquín Arias
, Sarat Chandra Varanasi, Kinjal Basu, Huaduo Wang, Fang Li, Serdar Erbatur, Parth Padalkar, Abhiramon Rajasekharan, Yankai Zeng, Manuel Carro:
Prolog: Past, Present, and Future. Prolog: The Next 50 Years 2023: 48-61 - [p1]Gopal Gupta, Huaduo Wang, Kinjal Basu, Farhad Shakerin, Elmer Salazar, Sarat Chandra Varanasi, Parth Padalkar, Sopam Dasgupta:
Logic-Based Explainable and Incremental Machine Learning. Prolog: The Next 50 Years 2023: 346-358 - [i10]Sopam Dasgupta, Farhad Shakerin, Joaquín Arias, Elmer Salazar, Gopal Gupta:
Counterfactual Explanation Generation with s(CASP). CoRR abs/2310.14497 (2023) - 2022
- [j4]Dhruva Pendharkar, Kinjal Basu
An ASP-based Approach to Answering Natural Language Questions for Texts. Theory Pract. Log. Program. 22(3): 419-443 (2022) - [j3]Huaduo Wang
FOLD-RM: A Scalable, Efficient, and Explainable Inductive Learning Algorithm for Multi-Category Classification of Mixed Data. Theory Pract. Log. Program. 22(5): 658-677 (2022) - [c11]Gopal Gupta, Elmer Salazar, Sarat Chandra Varanasi, Kinjal Basu, Joaquín Arias, Farhad Shakerin, Fang Li, Huaduo Wang:
Tutorial: Automating Commonsense Reasoning. ICLP Workshops 2022 - [i9]Huaduo Wang, Farhad Shakerin, Gopal Gupta:
FOLD-RM: A Scalable and Efficient Inductive Learning Algorithm for Multi-Category Classification of Mixed Data. CoRR abs/2202.06913 (2022) - 2021
- [c10]Kinjal Basu, Sarat Chandra Varanasi, Farhad Shakerin, Joaquín Arias, Gopal Gupta:
Knowledge-driven Natural Language Understanding of English Text and its Applications. AAAI 2021: 12554-12563 - [c9]Gopal Gupta, Sarat Varnasi, Kinjal Basu, Zhuo Chen, Elmer Salazar, Farhad Shakerin, Serdar Erbatur, Fang Li, Huaduo Wang, Joaquín Arias, Brendan Hall, Kevin Driscoll:
Formalizing Informal Logic and Natural Language Deductivism. ICLP Workshops 2021 - [i8]Kinjal Basu, Sarat Chandra Varanasi, Farhad Shakerin, Joaquín Arias, Gopal Gupta:
Knowledge-driven Natural Language Understanding of English Text and its Applications. CoRR abs/2101.11707 (2021) - [i7]Huaduo Wang, Farhad Shakerin, Gopal Gupta:
A Clustering and Demotion Based Algorithm for Inductive Learning of Default Theories. CoRR abs/2109.12624 (2021) - [i6]Dhruva Pendharkar, Kinjal Basu, Farhad Shakerin, Gopal Gupta:
An ASP-based Approach to Answering Natural Language Questions for Texts. CoRR abs/2112.11241 (2021) - 2020
- [j2]Farhad Shakerin
White-box Induction From SVM Models: Explainable AI with Logic Programming. Theory Pract. Log. Program. 20(5): 656-670 (2020) - [c8]Kinjal Basu
AQuA: ASP-Based Visual Question Answering. PADL 2020: 57-72 - [c7]Farhad Shakerin, Gopal Gupta:
Whitebox Induction of Default Rules Using High-Utility Itemset Mining. PADL 2020: 168-176 - [c6]Kinjal Basu, Sarat Chandra Varanasi, Farhad Shakerin, Gopal Gupta:
SQuARE: Semantics-based Question Answering and Reasoning Engine. ICLP Technical Communications 2020: 73-86 - [i5]Farhad Shakerin, Gopal Gupta:
White-box Induction From SVM Models: Explainable AI with Logic Programming. CoRR abs/2008.03301 (2020)
2010 – 2019
- 2019
- [c5]Farhad Shakerin, Gopal Gupta:
Induction of Non-Monotonic Logic Programs to Explain Boosted Tree Models Using LIME. AAAI 2019: 3052-3059 - [c4]Farhad Shakerin:
Induction of Non-monotonic Logic Programs To Explain Statistical Learning Models. ICLP Technical Communications 2019: 379-388 - [i4]Farhad Shakerin, Gopal Gupta:
Induction of Non-Monotonic Rules From Statistical Learning Models Using High-Utility Itemset Mining. CoRR abs/1905.11226 (2019) - 2018
- [c3]Farhad Shakerin, Gopal Gupta:
Cumulative Scoring-Based Induction of Default Theories. ICLP (Technical Communications) 2018: 2:1-2:15 - [c2]Farhad Shakerin, Gopal Gupta:
Heuristic Based Induction of Answer Set Programs, From Default theories to Combinatorial problems. ILP Up-and-Coming / Short Papers 2018: 36-51 - [i3]Farhad Shakerin, Gopal Gupta:
Heuristic Based Induction of Answer Set Programs: From Default theories to combinatorial problems. CoRR abs/1802.06462 (2018) - [i2]Farhad Shakerin, Gopal Gupta:
Induction of Non-Monotonic Logic Programs to Explain Boosted Tree Models Using LIME. CoRR abs/1808.00629 (2018) - 2017
- [j1]Farhad Shakerin
A new algorithm to automate inductive learning of default theories. Theory Pract. Log. Program. 17(5-6): 1010-1026 (2017) - [c1]Gopal Gupta, Elmer Salazar, Kyle Marple, Zhuo Chen, Farhad Shakerin:
A Case for Query-driven Predicate Answer Set Programming. ARCADE@CADE 2017: 64-68 - [i1]Farhad Shakerin, Elmer Salazar, Gopal Gupta:
A New Algorithm to Automate Inductive Learning of Default Theories. CoRR abs/1707.02693 (2017)
Coauthor Index
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