| Lexicase Selection Beyond Genetic Programming B Metevier, AK Saini, L Spector Genetic Programming Theory and Practice XVI, 123-136, 2019 | 37 | 2019 |
| Using modularity metrics as design features to guide evolution in genetic programming AK Saini, L Spector Genetic Programming Theory and Practice XVII, 165-180, 2020 | 10 | 2020 |
| Effect of parent selection methods on modularity AK Saini, L Spector Genetic Programming: 23rd European Conference, EuroGP 2020, Held as Part of …, 2020 | 8 | 2020 |
| Faster Convergence with Lexicase Selection in Tree-Based Automated Machine Learning N Matsumoto, AK Saini, P Ribeiro, H Choi, A Orlenko, LP Lyytikäinen, ... European Conference on Genetic Programming (Part of EvoStar), 165-181, 2023 | 5 | 2023 |
| Why and when are loops useful in genetic programming? AK Saini, L Spector Proceedings of the 2020 Genetic and Evolutionary Computation Conference …, 2020 | 5 | 2020 |
| Modularity metrics for genetic programming AK Saini, L Spector Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2019 | 5 | 2019 |
| Relationships between parent selection methods, looping constructs, and success rate in genetic programming AK Saini, L Spector Genetic Programming and Evolvable Machines 22, 495-509, 2021 | 3 | 2021 |
| TPOT2: A New Graph-Based Implementation of the Tree-Based Pipeline Optimization Tool for Automated Machine Learning P Ribeiro, A Saini, J Moran, N Matsumoto, H Choi, M Hernandez, ... Genetic Programming Theory and Practice XX, 1-17, 2024 | 2 | 2024 |
| Genetic Programming as an Innovation Engine for Automated Machine Learning: The Tree-Based Pipeline Optimization Tool (TPOT) JH Moore, PH Ribeiro, N Matsumoto, AK Saini Handbook of Evolutionary Machine Learning, 439-455, 2023 | 2 | 2023 |
| GLEAM: genetic learning by extraction and absorption of modules AK Saini, L Spector Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2021 | 2 | 2021 |
| Machine Learning—Automated Machine Learning (AutoML) for Disease Prediction JH Moore, PH Ribeiro, N Matsumoto, AK Saini Clinical Applications of Artificial Intelligence in Real-World Data, 161-173, 2023 | 1 | 2023 |
| Environments with local scopes for modules in genetic programming AK Saini, L Spector, T Helmuth Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2022 | 1 | 2022 |
| Evolving and Analyzing Modularity with GLEAM (Genetic Learning by Extraction and Absorption of Modules) AK Saini, L Spector Genetic Programming Theory and Practice XVIII, 181-195, 2022 | 1 | 2022 |
| Evaluating Bias-Mitigated Predictive Models of Perinatal Mood and Anxiety Disorders EF Wong, AK Saini, EE Accortt, MS Wong, JH Moore, TJ Bright JAMA Network Open 7 (12), e2438152-e2438152, 2024 | | 2024 |
| Lexicase Selection Parameter Analysis: Varying Population Size and Test Case Redundancy with Diagnostic Metrics JG Hernandez, AK Saini, JH Moore arXiv preprint arXiv:2407.15056, 2024 | | 2024 |
| Lexidate: Model Evaluation and Selection with Lexicase JG Hernandez, AK Saini, JH Moore Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2024 | | 2024 |
| Lexicase Selection Parameter Analysis: Varying Population Size and Test Case Redundancy with Diagnostic Metrics J Guadalupe Hernandez, AK Saini, JH Moore arXiv e-prints, arXiv: 2407.15056, 2024 | | 2024 |
| Lexidate: Model Evaluation and Selection with Lexicase J Guadalupe Hernandez, AK Saini, JH Moore arXiv e-prints, arXiv: 2406.12006, 2024 | | 2024 |
| LABELED MODULES IN PROGRAMS THAT EVOLVE AK Saini | | 2022 |
Lee SpectorProfessor of Computer Science, Amherst CollegeVerified email at amherst.edu
