Majdi M. Mafarja
Artificial Intelligence · 2017–2023
A researcher in the Science corpus: 9 papers; trusts 29 researchers and is trusted by 21 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 188 citations into it; #7,090 of 35,345 by trust here, #5,924 by citations
- Computational Theory and Mathematics — 124 citations into it; #2,259 of 12,182 by trust here, #1,813 by citations
- Computer Vision and Pattern Recognition — 37 citations into it
- Information Systems — 19 citations into it
- Evaluation & Benchmarks — 17 citations into it
- Biomedical Engineering — 15 citations into it
- Control and Systems Engineering — 10 citations into it
- Statistical Learning Theory — 9 citations into it
Whom Majdi M. Mafarja trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Seyedali Mirjalili
- J. Ross Quinlan
- Isabelle M Guyon
- Seyed Mohammad Mirjalili
- Eid Emary
- El-Ghazali Talbi
- Xin-She Yang
- Huan Liu
- Ron Kohavi
- Andrew Lewis
Who trusts Majdi M. Mafarja overall
- Tansel Dökeroğlu
- Prachi Agrawal
- Hattan F. Abutarboush
- Yanan Zhang
- Hossam Faris
- Ayça Deniz
- Essam H. Houssein
- Talari Ganesh
- Hakan Ezgi Kiziloz
- Qasem Al-Tashi
Papers from Majdi M. Mafarja's perspective
Ordered by how strongly the researchers Majdi M. Mafarja trusts endorse each paper. Same corpus, a different order for every researcher.
- No free lunch theorems for optimization
- A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms (Swarm and Evolutionary Computation)
- The Nature of Statistical Learning Theory
- ImageNet classification with deep convolutional neural networks
- Genetic Algorithms in Search Optimization and Machine Learning
- Swarm Intelligence (Lecture Notes in Computer Science)
- Induction of decision trees
- A study on the use of non-parametric tests for analyzing the evolutionary algorithms’ behaviour: a case study on the CEC’2005 Special Session on Real Parameter Optimization (J. Heuristics)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
Their papers
- Hybrid Whale Optimization Algorithm with simulated annealing for feature selection (2017) — 1,090 citations
- Evolutionary Population Dynamics and Grasshopper Optimization approaches for feature selection problems (2017) — 390 citations
- An efficient binary Salp Swarm Algorithm with crossover scheme for feature selection problems (2018) — 595 citations
- Whale optimization approaches for wrapper feature selection (2018) — 738 citations
- Binary dragonfly optimization for feature selection using time-varying transfer functions (2018) — 369 citations
- RIME: A physics-based optimization (2023) — 912 citations
- Metaphor-free dynamic spherical evolution for parameter estimation of photovoltaic modules (2021) — 56 citations
- Binary grasshopper optimisation algorithm approaches for feature selection problems (2019) — 378 citations
- Harris hawks optimization: Algorithm and applications (2019) — 5,546 citations