← Authors

Alexey Ignatiev

19 papers · 2015–2024 · 4 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (15) 🌍 Conference Polyglot (4) πŸƒ Academic Marathon (9) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (23) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🀝 Dynamic Duo (18) 🧬 Topic Evolution πŸ† Keyword Champion (3) πŸ”¬ Deep Specialist (11) πŸ—ƒοΈ Keyword Collector (67) πŸš€ Conference Pioneer πŸ’Ž Century Club (19) πŸ”₯ Unstoppable (8)

Conferences

AAAI (8) IJCAI (8) NIPS (2) ICML (1)

Top co-authors

Joao Marques-Silva (18) Nina Narodytska (8) Peter J. Stuckey (5) Yacine Izza (4) Antonio Morgado (4) Martin Cooper (2) Thomas Gerspacher (2) Martin C Cooper (1) MikolΓ‘Ε‘ Janota (1) Georg Weissenbacher (1)

Keywords

explainable ai (5) formal explanation (4) explainable artificial intelligence (4) decision tree (4) polynomial time (3) model explanation (3) abductive reasoning (3) model interpretability (2) model-based diagnosis (2) formal methods (2) black-box model (2) interpretable machine learning (2) post-hoc explanation (2) linear classifier (1) tree ensemble (1) rule learning (1) knowledge compilation (1) counterfactual explanation (1) integer linear programming (1) interpretable model (1)

Papers

Delivering Inflated Explanations AAAI 2024
On Tackling Explanation Redundancy in Decision Trees (Extended Abstract) IJCAI 2023
Eliminating the Impossible, Whatever Remains Must Be True: On Extracting and Applying Background Knowledge in the Context of Formal Explanations AAAI 2023
Delivering Trustworthy AI through Formal XAI AAAI 2022
Using MaxSAT for Efficient Explanations of Tree Ensembles AAAI 2022
Tractable Explanations for d-DNNF Classifiers AAAI 2022
Constraint-Driven Explanations for Black-Box ML Models AAAI 2022
A Scalable Two Stage Approach to Computing Optimal Decision Sets AAAI 2021
Explanations for Monotonic Classifiers. ICML 2021
Reasoning-Based Learning of Interpretable ML Models IJCAI 2021
Towards Trustable Explainable AI IJCAI 2020
Explaining Naive Bayes and Other Linear Classifiers with Polynomial Time and Delay NIPS 2020
Abduction-Based Explanations for Machine Learning Models AAAI 2019
On Relating Explanations and Adversarial Examples NIPS 2019
Model-Based Diagnosis with Multiple Observations IJCAI 2019
Learning Optimal Decision Trees with SAT IJCAI 2018
Cardinality Encodings for Graph Optimization Problems IJCAI 2017
Efficient Model Based Diagnosis with Maximum Satisfiability IJCAI 2015
Prime Compilation of Non-Clausal Formulae IJCAI 2015