From bf5b05a84e877391fddd1b0a0b752f71ec05e901 Mon Sep 17 00:00:00 2001 From: Jan Aalmoes Date: Wed, 11 Sep 2024 00:10:50 +0200 Subject: Preuve existe f pas cca equivalant exists f BA pas randomguess --- synthetic/biblio.bib | 387 +++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 387 insertions(+) create mode 100644 synthetic/biblio.bib (limited to 'synthetic/biblio.bib') diff --git a/synthetic/biblio.bib b/synthetic/biblio.bib new file mode 100644 index 0000000..6ee7f50 --- /dev/null +++ b/synthetic/biblio.bib @@ -0,0 +1,387 @@ +@misc{carlini2022membershipinferenceattacksprinciples, + title={Membership Inference Attacks From First Principles}, + author={Nicholas Carlini and Steve Chien and Milad Nasr and Shuang Song and Andreas Terzis and Florian Tramer}, + year={2022}, + eprint={2112.03570}, + archivePrefix={arXiv}, + primaryClass={cs.CR}, + url={https://arxiv.org/abs/2112.03570}, +} + +@article{brayne2015predictive, + title={Predictive policing}, + author={Brayne, Sarah and Rosenblat, Alex and Boyd, Danah}, + journal={Data \& Civil Rights: A New Era Of Policing And Justice}, + pages={2015--1027}, + year={2015} +} + +@inproceedings{barthelemy:hal-01837361, + TITLE = {{Pl@ntNet, une plate-forme innovante d'agr{\'e}gation et partage d'observations botaniques}}, + AUTHOR = {Barth{\'e}l{\'e}my, Daniel and Boujemaa, Nozha and Molino, Jean-Fran{\c c}ois and Joly, Alexis and Go{\"e}au, Herv{\'e} and Baki{\'c}, Vera and Selmi, Souheil and Champ, Julien and Carre, Jennifer and Chouet, Mathias and Perronnet, Aur{\'e}lien and Vignau, Christelle and Dufour-Kowalski, Samuel and Affouard, Antoine and Barbe, Julien and Bonnet, Pierre}, + URL = {https://hal.science/hal-01837361}, + BOOKTITLE = {{International Conference ‘Botanists of the Twenty-first Century'}}, + ADDRESS = {Paris, France}, + ORGANIZATION = {{UNESCO}}, + HAL_LOCAL_REFERENCE = {DEVMP}, + EDITOR = {No{\"e}line R. Rakotoarisoa and Stephen Blackmore and Bernard Riera}, + PAGES = {191-197}, + YEAR = {2014}, + MONTH = Sep, + KEYWORDS = {Pl@ntNet ; Botany ; Plateforme participative ; Observations botaniques}, + PDF = {https://hal.science/hal-01837361/file/DB_etal_plantnet_plateforme_2016_1.pdf}, + HAL_ID = {hal-01837361}, + HAL_VERSION = {v1}, +} + +@misc{plantnet, + title={Pl@ntNet}, + howpublished={\url{https://identify.plantnet.org/}}, + note={Dernier accès: 2024-07-24} +} + + +@article{dunn2018wearables, + title={Wearables and the medical revolution}, + author={Dunn, Jessilyn and Runge, Ryan and Snyder, Michael}, + journal={Personalized medicine}, + volume={15}, + number={5}, + pages={429--448}, + year={2018}, + publisher={Taylor \& Francis} +} + +@misc{gtrend, + title={Google trend Intelligence Artificielle}, + howpublished={\url{https://trends.google.com/trends/explore?date=all&geo=FR&q=intelligence%20artificielle&hl=en-US}}, + note={Dernier accès: 2024-07-24} +} + +@misc{france2030, + title={France 2030}, + howpublished={\url{https://www.info.gouv.fr/grand-dossier/france-2030}}, + note={Dernier accès: 2024-07-24} +} + +@misc{stratfr, + title={La stratégie nationale pour l'intelligence artificielle}, + howpublished={\url{https://www.entreprises.gouv.fr/fr/numerique/enjeux/la-strategie-nationale-pour-l-ia}}, + note={Dernier accès: 2024-07-24} +} + +@misc{applewatch, + title={WatchOS 11 brings powerful health and fitness insights, and even more personalization and connectivity }, + howpublished={\url{https://www.apple.com/newsroom/2024/06/watchos-11-brings-powerful-health-and-fitness-insights/}}, + note={Dernier accès: 2024-07-24} +} + +%%%%%%%%%%%CLIMATE CHANGE BACKGROUND +@article{barnes2019viewing, + title={Viewing forced climate patterns through an AI lens}, + author={Barnes, Elizabeth A and Hurrell, James W and Ebert-Uphoff, Imme and Anderson, Chuck and Anderson, David}, + journal={Geophysical Research Letters}, + volume={46}, + number={22}, + pages={13389--13398}, + year={2019}, + publisher={Wiley Online Library} +} + +@article{slater2023hybrid, + title={Hybrid forecasting: blending climate predictions with AI models}, + author={Slater, Louise J and Arnal, Louise and Boucher, Marie-Am{\'e}lie and Chang, Annie Y-Y and Moulds, Simon and Murphy, Conor and Nearing, Grey and Shalev, Guy and Shen, Chaopeng and Speight, Linda and others}, + journal={Hydrology and earth system sciences}, + volume={27}, + number={9}, + pages={1865--1889}, + year={2023}, + publisher={Copernicus Publications G{\"o}ttingen, Germany} +} + +%%%%%%%%%%%%ENERGY BACKGROUND +@article{jin2020energy, + title={Energy and AI}, + author={Jin, Donghan and Ocone, Raffaella and Jiao, Kui and Xuan, Jin}, + journal={Energy and AI}, + volume={1}, + pages={100002}, + year={2020}, + publisher={Elsevier} +} + +@article{kumar2020distributed, + title={Distributed energy resources and the application of AI, IoT, and blockchain in smart grids}, + author={Kumar, Nallapaneni Manoj and Chand, Aneesh A and Malvoni, Maria and Prasad, Kushal A and Mamun, Kabir A and Islam, FR and Chopra, Shauhrat S}, + journal={Energies}, + volume={13}, + number={21}, + pages={5739}, + year={2020}, + publisher={MDPI} +} + +@article{kumari2020blockchain, + title={Blockchain and AI amalgamation for energy cloud management: Challenges, solutions, and future directions}, + author={Kumari, Aparna and Gupta, Rajesh and Tanwar, Sudeep and Kumar, Neeraj}, + journal={Journal of Parallel and Distributed Computing}, + volume={143}, + pages={148--166}, + year={2020}, + publisher={Elsevier} +} + +@article{ngarambe2020use, + title={The use of artificial intelligence (AI) methods in the prediction of thermal comfort in buildings: Energy implications of AI-based thermal comfort controls}, + author={Ngarambe, Jack and Yun, Geun Young and Santamouris, Mat}, + journal={Energy and Buildings}, + volume={211}, + pages={109807}, + year={2020}, + publisher={Elsevier} +} + + +%%%%%OPEN AI + +@misc{openaibfm, + title={OpenAI, cette société qui révolutionne l'intelligence artificielle}, + howpublished={\url{https://www.bfmtv.com/tech/intelligence-artificielle/open-ai-cette-societe-qui-revolutionne-l-intelligence-artificielle_DN-202311200564.html}}, + note={Dernier accès: 2024-07-24} +} + +@misc{openaiinter, + title={Intelligence artificielle : pourquoi Sam Altman, créateur de ChatGPT, a été débarqué d'OpenAI}, + howpublished={\url{https://www.radiofrance.fr/franceinter/ce-que-l-on-sait-du-renvoi-de-sam-altman-patron-d-openai-et-createur-de-chatgpt-5672369}}, + note={Dernier accès: 2024-07-24} +} + +@misc{openaint, + title={OpenAI Says It Has Begun Training a New Flagship A.I. Model}, + howpublished={\url{https://www.nytimes.com/2024/05/28/technology/openai-gpt4-new-model.html}}, + note={Dernier accès: 2024-07-24} +} + +@misc{openaibg, + title={ChatGPT sets record for fastest-growing user base - analyst note}, + howpublished={\url{https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/}}, + note={Dernier accès: 2024-07-24} +} + +@misc{gptjournal, + title={ChatGPT : le quotidien Le Monde signe un partenariat avec OpenAI, une première en France}, + howpublished={\url{https://www.radiofrance.fr/franceinter/podcasts/l-info-de-france-inter/les-doc-france-inter-du-jeudi-14-mars-3-7619379}}, + note={Dernier accès: 2024-07-24} +} + +@article{beraja2023ai, + title={AI-tocracy}, + author={Beraja, Martin and Kao, Andrew and Yang, David Y and Yuchtman, Noam}, + journal={The Quarterly Journal of Economics}, + volume={138}, + number={3}, + pages={1349--1402}, + year={2023}, + publisher={Oxford University Press} +} + + + + + +@misc{song2020overlearning, + title={Overlearning Reveals Sensitive Attributes}, + author={Congzheng Song and Vitaly Shmatikov}, + year={2020}, + eprint={1905.11742}, + archivePrefix={arXiv}, + primaryClass={cs.LG} +} + +@article{EO, + author = {Moritz Hardt and + Eric Price and + Nathan Srebro}, + title = {Equality of Opportunity in Supervised Learning}, + journal = {CoRR}, + volume = {abs/1610.02413}, + year = {2016}, + url = {http://arxiv.org/abs/1610.02413}, + eprinttype = {arXiv}, + eprint = {1610.02413}, + timestamp = {Tue, 26 Apr 2022 09:17:17 +0200}, + biburl = {https://dblp.org/rec/journals/corr/HardtPS16.bib}, + bibsource = {dblp computer science bibliography, https://dblp.org} +} + +@article{hawkins2004problem, + title={The problem of overfitting}, + author={Hawkins, Douglas M}, + journal={Journal of chemical information and computer sciences}, + volume={44}, + number={1}, + pages={1--12}, + year={2004}, + publisher={ACS Publications} +} + +@misc{yeom, + title={Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting}, + author={Samuel Yeom and Irene Giacomelli and Matt Fredrikson and Somesh Jha}, + year={2018}, + eprint={1709.01604}, + archivePrefix={arXiv}, + primaryClass={cs.CR} +} + +@misc{vgg16, + title={Very Deep Convolutional Networks for Large-Scale Image Recognition}, + author={Karen Simonyan and Andrew Zisserman}, + year={2015}, + eprint={1409.1556}, + archivePrefix={arXiv}, + primaryClass={cs.CV}, + url={https://arxiv.org/abs/1409.1556}, +} +@misc{CGAN, + title={Conditional Generative Adversarial Nets}, + author={Mehdi Mirza and Simon Osindero}, + year={2014}, + eprint={1411.1784}, + archivePrefix={arXiv}, + primaryClass={cs.LG}, + url={https://arxiv.org/abs/1411.1784}, +} +@ARTICLE{cnn, + + author={Rawat, Waseem and Wang, Zenghui}, + + journal={Neural Computation}, + + title={Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review}, + + year={2017}, + + volume={29}, + + number={9}, + + pages={2352-2449}, + + keywords={}, + + doi={10.1162/neco_a_00990}} + +@misc{dcgan, + title={Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks}, + author={Alec Radford and Luke Metz and Soumith Chintala}, + year={2016}, + eprint={1511.06434}, + archivePrefix={arXiv}, + primaryClass={cs.LG}, + url={https://arxiv.org/abs/1511.06434} +} +@inproceedings{gan, +author = {Goodfellow, Ian J. and Pouget-Abadie, Jean and Mirza, Mehdi and Xu, Bing and Warde-Farley, David and Ozair, Sherjil and Courville, Aaron and Bengio, Yoshua}, +title = {Generative adversarial nets}, +year = {2014}, +publisher = {MIT Press}, +address = {Cambridge, MA, USA}, +booktitle = {Proceedings of the 27th International Conference on Neural Information Processing Systems - Volume 2}, +pages = {2672–2680}, +numpages = {9}, +location = {Montreal, Canada}, +series = {NIPS'14} +} +@misc{ctgan, + title={Modeling Tabular data using Conditional GAN}, + author={Lei Xu and Maria Skoularidou and Alfredo Cuesta-Infante and Kalyan Veeramachaneni}, + year={2019}, + eprint={1907.00503}, + archivePrefix={arXiv}, + primaryClass={cs.LG}, + url={https://arxiv.org/abs/1907.00503}, +} +@article{bellovin2019privacy, + title={Privacy and synthetic datasets}, + author={Bellovin, Steven M and Dutta, Preetam K and Reitinger, Nathan}, + journal={Stan. Tech. L. Rev.}, + volume={22}, + pages={1}, + year={2019}, + publisher={HeinOnline} +} + +@inproceedings{ping2017datasynthesizer, + title={Datasynthesizer: Privacy-preserving synthetic datasets}, + author={Ping, Haoyue and Stoyanovich, Julia and Howe, Bill}, + booktitle={Proceedings of the 29th International Conference on Scientific and Statistical Database Management}, + pages={1--5}, + year={2017} +} + +@inproceedings{kuppa2021towards, + title={Towards improving privacy of synthetic datasets}, + author={Kuppa, Aditya and Aouad, Lamine and Le-Khac, Nhien-An}, + booktitle={Annual Privacy Forum}, + pages={106--119}, + year={2021}, + organization={Springer} +} + +@article{tai2023user, + title={User-Driven Synthetic Dataset Generation with Quantifiable Differential Privacy}, + author={Tai, Bo-Chen and Tsou, Yao-Tung and Li, Szu-Chuang and Huang, Yennun and Tsai, Pei-Yuan and Tsai, Yu-Cheng}, + journal={IEEE Transactions on Services Computing}, + year={2023}, + publisher={IEEE} +} +@article{stadler2020synthetic, + title={Synthetic data-A privacy mirage}, + author={Stadler, Theresa and Oprisanu, Bristena and Troncoso, Carmela}, + journal={arXiv preprint arXiv:2011.07018}, + year={2020}, + publisher={Nov} +} + +@inproceedings{jordon2021hide, + title={Hide-and-seek privacy challenge: Synthetic data generation vs. patient re-identification}, + author={Jordon, James and Jarrett, Daniel and Saveliev, Evgeny and Yoon, Jinsung and Elbers, Paul and Thoral, Patrick and Ercole, Ari and Zhang, Cheng and Belgrave, Danielle and van der Schaar, Mihaela}, + booktitle={NeurIPS 2020 Competition and Demonstration Track}, + pages={206--215}, + year={2021}, + organization={PMLR} +} + +@inproceedings{abadi2016deep, + title={Deep learning with differential privacy}, + author={Abadi, Martin and Chu, Andy and Goodfellow, Ian and McMahan, H Brendan and Mironov, Ilya and Talwar, Kunal and Zhang, Li}, + booktitle={Proceedings of the 2016 ACM SIGSAC conference on computer and communications security}, + pages={308--318}, + year={2016} +} + +@inproceedings{shokri2017membership, + title={Membership inference attacks against machine learning models}, + author={Shokri, Reza and Stronati, Marco and Song, Congzheng and Shmatikov, Vitaly}, + booktitle={2017 IEEE symposium on security and privacy (SP)}, + pages={3--18}, + year={2017}, + organization={IEEE} +} + +@article{ding2021retiring, + title={Retiring Adult: New Datasets for Fair Machine Learning}, + author={Ding, Frances and Hardt, Moritz and Miller, John and Schmidt, Ludwig}, + journal={Advances in Neural Information Processing Systems}, + volume={34}, + year={2021} +} + +@inproceedings{zhifei2017cvpr, + title={Age Progression/Regression by Conditional Adversarial Autoencoder}, + author={Zhang, Zhifei and Song, Yang and Qi, Hairong}, + booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, + year={2017}, + organization={IEEE} +} -- cgit v1.2.3