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Sustainable AI is a subfield of AI for concerning developing and using AI systems in ways of aiming to reduce environmental impact and achieve sustainability.
Smote: synthetic minority over-sampling technique
Chawla N V, Bowyer K W, Hall L O, Kegelmeyer W P · 2002
Earlier work this paper cites.
Training cost-sensitive neural networks with methods addressing the class imbalance problem
Zhou Z H, Liu X Y · 2005
Earlier work this paper cites.
Robust de-anonymization of large sparse datasets
Narayanan A, Shmatikov V · 2008
Earlier work this paper cites.
Differential privacy
Dwork C · 2008
Earlier work this paper cites.
Learning from imbalanced data
He H, Garcia E A · 2009
Earlier work this paper cites.
An iterative and re-weighting framework for rejection and uncertainty resolution in crowdsourcing
Xie S, Fan W, Yu P S · 2012
Earlier work this paper cites.
Internet of things (iot): A vision, architectural elements, and future directions
Gubbi J, Buyya R, Marusic S, Palaniswami M · 2013
Earlier work this paper cites.
Using openrefine
Verborgh R, De Wilde M · 2013
Earlier work this paper cites.
Ethereum: A Secure Decentralized Generalized Transaction Ledger
Wood G · 2014
Earlier work this paper cites.
Efficient fully homomorphic encryption from (standard) lwe
Brakerski Z, Halevi S, Smart N P · 2014
Earlier work this paper cites.
A survey of sustainable ai scalability techniques
Stoica I, Zaharia M, Ghodsi A · 2014
Earlier work this paper cites.
Privacy, surveillance, and public trust
Regan P M · 2015
Earlier work this paper cites.
Deep feature synthesis: Towards automating data science endeavors
Kanter J M, Veeramachaneni K · 2015
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Data cleaning: Overview and emerging challenges
Chu X, Ilyas I F, Krishnan S, Wang J · 2016
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Membership inference attacks against machine learning models
Shokri R, Stronati M, Song C, Shmatikov V · 2017
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Mining non-textual data for deep learning models
Sun X, Leskovec J · 2017
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Truth inference in crowdsourcing: Is the problem solved?
Zheng Y, Li G, Li Y, Shan C, Cheng R · 2017
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Communication-efficient learning of deep networks from decentralized data
McMahan B, Moore E, Ramage D · 2017
Cited alongside, same era.
Alphaclean: Automatic generation of data cleaning pipelines
Krishnan S, Wu E · 2019
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Autoaugment: Learning augmentation strategies from data
Cubuk E D, Zoph B, Mane D, Vasudevan V, Le Q V · 2019
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Synthetic data generation for privacy-preserving machine learning
Franklin A, Cook J D · 2020
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Ai for environmental monitoring: Applications and challenges
Xu J, Liu Q, Liu Y · 2020
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Homomorphic encryption for privacy-preserving machine learning: A survey
Chen X, Liu S, Xiong H · 2020
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The international data spaces initiative: A blueprint for secure data sharing
Bohnenberger M, Behrens L D P, Flemming R S · 2021
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Data management in machine learning: Challenges, techniques, and systems
Kumar A, Boehm M, Yang J · 2017
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Active learning for convolutional neural networks: A core-set approach
Sener O, Savarese S · 2017
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Gender shades: Intersectional accuracy disparities in commercial gender classification
Buolamwini J, Gebru T · 2018
Cited alongside, same era.
Energy and policy considerations for deep learning in nlp
Strubell R, Ganesh A, McCallum A · 2019
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Waymo’s approach to self-driving car development
Waymo · 2019
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The healthdataspace project: Enabling secure cross-border health data sharing for ai applications
Consortium H · 2021
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The standardization of non-textual data for ai systems: Challenges and opportunities
Herzog T, Ochoa M T L M · 2021
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A survey of data augmentation approaches for nlp
Feng S Y, Gangal V, Wei J, Chandar S, Vosoughi S, Mitamura T, Hovy E · 2021
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In defense of core-set: A density-aware core-set selection for active learning
Kim Y, Shin B · 2022
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Log-based anomaly detection with deep learning: How far are we?
Le V H, Zhang H · 2022
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