paper.bib

@article{NAS-1000-paper-review,  
    title={Neural Architecture Search: Insights from 1000 Papers},
    author={Colin White and Mahmoud Safari and Rhea Sukthanker and Binxin Ru and Thomas Elsken and Arber Zela and Debadeepta Dey and Frank Hutter},
    journal={arXiv e-prints},
    year={2023},
    archivePrefix={arXiv},
    eprint={2301.08727},
    primaryClass={cs.LG},
    doi={10.48550/arXiv.2301.08727},
}

@article{NAS-review-efficient-performance-prediction,
    title={A survey on computationally efficient neural architecture search},
    author={Liu, Shiqing and Zhang, Haoyu and Jin, Yaochu},
    journal={Journal of Automation and Intelligence},
    volume={1},
    number={1},
    pages={100002},
    year={2022},
    doi={10.1016/j.jai.2022.100002},
}

@article{EvoNAS-survey,
    title={A Survey on Evolutionary Neural Architecture Search},
    author={Liu, Yuqiao and Sun, Yanan and Xue, Bing and Zhang, Mengjie and Yen, Gary G. and Tan, Kay Chen},
    year={2023},
    journal={IEEE Transactions on Neural Networks and Learning Systems},
    volume={34},    
    number={2},
    pages={550–570},
    doi={10.1109/TNNLS.2021.3100554},
}

@article{evolutionary-computation,
    title={Evolutionary computing},
    author={A.E. Eiben and M. Schoenauer},
    year={2002},
    journal={Information Processing Letters},
    volume={82},
    number={1},
    pages={1-6},
    doi={10.1016/S0020-0190(02)00204-1},
}

@inproceedings{EvoNAS-survey-advacements,
    title={A Survey of Advances in Evolutionary Neural Architecture Search},
    author={Zhou, Xun and Qin, A. K. and Sun, Yanan and Tan, Kay Chen},
    booktitle={2021 IEEE Congress on Evolutionary Computation (CEC)}, 
    pages={950-957},
    year={2021},
    organization={IEEE},
    doi={10.1109/CEC45853.2021.9504890},
}

@article{optimization-algorithms,
    title={Review of optimization techniques},
    author={Venter, Gerhard},
    year={2010},
    journal={Encyclopedia of aerospace engineering},
    doi={10019.1/14646},
}

@article{evolutionary-algorithm, 
    title={Evolutionary algorithms}, 
    author={Bartz‐Beielstein, Thomas and Branke, Jürgen and Mehnen, Jörn and Mersmann, Olaf}, 
    year={2014}, 
    journal={WIREs Data Mining and Knowledge Discovery}, 
    volume={4}, 
    number={3}, 
    pages={178–195},
    doi={10.1002/widm.1124},
} 

@inproceedings{EvoNAS-NSGA-Net-multi-obj,
    title = {NSGA-Net: neural architecture search using multi-objective genetic algorithm},
    author = {Lu, Zhichao and Whalen, Ian and Boddeti, Vishnu and Dhebar, Yashesh and Deb, Kalyanmoy and Goodman, Erik and Banzhaf, Wolfgang},
    booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference},
    pages={419--427},
    year = {2019},
    doi={10.1145/3321707.3321729},
}

@inproceedings{EvoNAS-rene, 
    title={End-to-end evolutionary neural architecture search for microcontroller units},
    author={Groh, René and Kist, Andreas M.},
    booktitle={2023 IEEE International Conference on Omni-layer Intelligent Systems (COINS)},
    pages={1--7},
    volume={},
    number={},
    year={2023},
    organization={IEEE},
    doi={10.1109/COINS57856.2023.10189194},
}

@inproceedings{EvoNAS-regularized-evolution-img-classifier, 
    title={Regularized Evolution for Image Classifier Architecture Search}, 
    author={Real, Esteban and Aggarwal, Alok and Huang, Yanping and Le, Quoc V},
    booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
    volume={33},
    number={01},
    pages={4780--4789},
    year={2019},
    doi={10.1609/aaai.v33i01.33014780},
}

@article{EvoNAS-CNN-design,
    title={Automatically Designing CNN Architectures Using the Genetic Algorithm for Image Classification}, 
    author={Sun, Yanan and Xue, Bing and Zhang, Mengjie and Yen, Gary G. and Lv, Jiancheng},
    year={2020},
    journal={IEEE Transactions on Cybernetics}, 
    volume={50},
    number={9},
    pages={3840-3854},  
    doi={10.1109/TCYB.2020.2983860}
}

# Not sure if this cited correctly  
@book{evolution-darwin,
  title={The Origin of Species by Means of Natural Selection: Or, The Preservation of Favored Races in the Struggle for Life},
  author={Darwin, Charles and Burrow, John W},
  year={2009},
  publisher={AL Burt},
  address={New York, United States},
  pages={441--764}
}

@article{NAS-survey-new,
    title={Neural architecture search: A survey},
    author={Elsken, Thomas and Metzen, Jan Hendrik and Hutter, Frank},
    journal={Journal of Machine Learning Research},
    year={2019},
    volume={20},
    number={55},
    pages={1--21},
}

@InProceedings{EvoNAS-large-scale-evolution-img-classifier,
    title={Large-Scale Evolution of Image Classifiers},
    author={Esteban Real and Sherry Moore and Andrew Selle and Saurabh Saxena and Yutaka Leon Suematsu and Jie Tan and Quoc V. Le and Alexey Kurakin},
    booktitle={Proceedings of the 34th International Conference on Machine Learning},
    volume={70},    
    pages={2902--2911},
    year={2017},
    organization={PMLR}
}

@inproceedings{EvoNAS-fast-denser,
    title={Fast DENSER: Efficient Deep NeuroEvolution},
    author={Assun{\c{c}}{\~a}o, Filipe and Louren{\c{c}}o, Nuno and Machado, Penousal and Ribeiro, Bernardete},
    booktitle={Genetic Programming},
    pages={197--212},
    year={2019},
    doi={10.1007/978-3-030-16670-0_13},
}

@article{pareto-optimality,
    title={Clustering Analysis for the Pareto Optimal Front in Multi-Objective Optimization},
    author={Bejarano, Lilian Astrid and Espitia, Helbert Eduardo and Montenegro, Carlos Enrique},
    journal={Computation},
    volume={10},
    number={3},
    article-number={37},
    year={2022},
    publisher={MDPI},
    doi={10.3390/computation10030037},
}

@inproceedings{EvoNAS-lemonade-multi-objective,
    author={Elsken, Thomas and Metzen, Jan Hendrik and Hutter, Frank},
    title={Efficient Multi-Objective Neural Architecture Search via Lamarckian Evolution},
    booktitle={International Conference on Learning Representations},
    year={2019},
    doi={10.48550/arXiv.1804.09081},
}

@inproceedings{EvoNAS-human-sketches,
    title={Deep convolutional networks for human sketches by means of the evolutionary deep learning},
    author={Fujino, Saya and Mori, Naoki and Matsumoto, Keinosuke},
    booktitle={2017 joint 17th world congress of international fuzzy systems association and 9th international conference on soft computing and intelligent systems (IFSA-SCIS)},
    volume={},
    number={},
    pages={1-5},
    year={2017},
    doi={10.1109/IFSA-SCIS.2017.8023302},
}

@article{NAS-survey, 
    author={Ren, Pengzhen and Xiao, Yun and Chang, Xiaojun and Huang, Po-yao and Li, Zhihui and Chen, Xiaojiang and Wang, Xin}, 
    title={A comprehensive survey of neural architecture search}, 
    journal={ACM Computing Surveys},
    year={2021},
    volume={54},
    number={4}, 
    pages={1–34},
    doi={10.1145/3447582},
} 

@inproceedings{NAS-random-search,
    title = {Random Search and Reproducibility for Neural Architecture Search},
    author = {Li, Liam and Talwalkar, Ameet},
    booktitle = {Proceedings of The 35th Uncertainty in Artificial Intelligence Conference},
    pages = {367--377},
    year = {2020},
    volume = {115},
}

% not sure if this is cited correctly (https://infoscience.epfl.ch/record/273463?ln=fr&v=pdf)
@inproceedings{NAS-search-strategy,
    title={Evaluating the search phase of neural architecture search},
    author={Yu, Kaicheng and Suito, Christian and Jaggi, Martin and Musat, Claudiu-Cristian and Salzmann, Mathieu},
    booktitle={ICRL 2020 Eighth International Conference on Learning Representations},
    year={2020},
    doi={20.500.14299/164236}
}

@article{tensorboard,
    title={A Tour of TensorFlow}, 
    author={Peter Goldsborough},
    journal = {arXiv e-prints},
    year={2016},
    eprint={1610.01178},
    archivePrefix={arXiv},
    primaryClass={cs.LG},
    doi={10.48550/arXiv.1610.01178}
}

@inproceedings{ML-tracking-frameworks,
    title={Comparison of experiment tracking frameworks in machine learning environments},
    author={Budras, Tim and Blanck, Maximilian and Berger, Tilman and Schmidt, Andreas},
    booktitle={Proceedings of the Fourteenth International Conference on Advances in Databases, Knowledge, and Data Applications},
    pages={21--28},
    year={2022}
}

@inproceedings{EvoVis-alternative,
    title={Visualization System for Evolutionary Neural Networks for Deep Learning}, 
    author={Chae, Junghoon and Schuman, Catherine D and Young, Steven R and Johnston, J Travis and Rose, Derek C and Patton, Robert M and Potok, Thomas E},
    booktitle={2019 IEEE International Conference on Big Data (Big Data)},
    pages={4498--4502},
    year={2019},
    doi={10.1109/BigData47090.2019.9006470},
}

@inproceedings{ml-reproducability,
    title={A Taxonomy of Tools for Reproducible Machine Learning Experiments},
    author={Quaranta, Luigi and Calefato, Fabio and Lanubile, Filippo and others},
    booktitle={CEUR Workshop Proceedings},
    volume={3078},
    pages={65--76},
    year={2022},
    url={https://ricerca.uniba.it/handle/11586/380827}
}

@article{cytoscape-js,
    author = {Franz, Max and Lopes, Christian T. and Huck, Gerardo and Dong, Yue and Sumer, Onur and Bader, Gary D.},
    title = {Cytoscape.js: a graph theory library for visualisation and analysis},
    journal = {Bioinformatics},
    volume = {32},
    number = {2},
    pages = {309-311},
    year = {2015},   
    doi={10.1093/bioinformatics/btv557}
}

@article{python-trends,
    title={Python current trend applications-an overview},
    author={Saabith, AS and Fareez, MMM and Vinothraj, T},
    journal={International Journal of Advance Engineering and Research Development},
    volume={6},
    number={10},
    year={2019}
}

@inproceedings{NAS-reinforcement-learning,
    title={Neural Architecture Search with Reinforcement Learning},
    author={Zoph, Barret and Le, Quoc},
    booktitle={International Conference on Learning Representations},
    year={2016}
}

@inproceedings{NAS-BANANAS,
    title={Bananas: Bayesian optimization with neural architectures for neural architecture search},
    author={White, Colin and Neiswanger, Willie and Savani, Yash},
    booktitle={Proceedings of the AAAI conference on artificial intelligence},
    volume={35},
    number={12},
    pages={10293--10301},
    year={2021},
    doi={10.1609/aaai.v35i12.17233},
}

@article{lecun2015deep,
    title={Deep learning},
    author={LeCun, Yann and Bengio, Yoshua and Hinton, Geoffrey},
    journal={nature},
    volume={521},
    number={7553},
    pages={436--444},
    year={2015},
    publisher={Nature Publishing Group UK London},
    doi={10.1038/nature14539},
}