Fetching the paper…
Reading the bibliography…
Our research endeavors to advance the concept of responsible artificial intelligence (AI), a topic of increasing importance within EU policy discussions.
Systematic literature reviews in software engineering – A systematic literature review
Kitchenham B, Brereton OP, Budgen D, Turne M, Bailey J, Linkman S · 2009
Earlier work this paper cites.
What is data ethics?
Floridi L, Taddeo M · 2016
Earlier work this paper cites.
AI4People—an ethical framework for a good AI society: opportunities, risks, principles, and recommendations
Floridi L, Cowls J, Beltrametti M, Chatila R, Chazerand P, Dignum V, et al · 2018
Earlier work this paper cites.
Available from: https://digital-strategy.ec.europa.eu/en/policies/expert-group-ai
European Commission. Ethics guidelines for trustworthy AI e. European Commission.; 2019 · 2019
Earlier work this paper cites.
Available from: https://digital-strategy.ec.europa.eu/en/library/communication-fostering-european-approach-artificial-intelligence
European Commission. White Paper on Artificial Intelligence A European approach to excellence and trust. European Commission,.; 2020 · 2020
Earlier work this paper cites.
Towards Responsible AI for Financial Transactions
Maree C, Modal JE, Omlin CW · 2020
Earlier work this paper cites.
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
Alejandro Barredo Arrieta, Natalia Díaz-Rodríguez, Javier Del Ser, Adrien Bennetot, Siham Tabik, Alberto Barbado, et al · 2020
Earlier work this paper cites.
Trustworthiness of Artificial Intelligence
Jain S, Luthra M, Sharma S, Fatima M · 2020
Earlier work this paper cites.
Trustworthy AI in the Age of Pervasive Computing and Big Data
Kumar A, Braud T, Tarkoma S, Hui P · 2020
Earlier work this paper cites.
A Comparative Assessment and Synthesis of Twenty Ethics Codes on AI and Big Data
Loi M, Heitz C, Christen M · 2020
Earlier work this paper cites.
Principled artificial intelligence: Mapping consensus in ethical and rights-based approaches to principles for AI
Fjeld J, Achten N, Hilligoss H, Nagy A, Srikumar M · 2020
Earlier work this paper cites.
Bridging the Gap Between Ethics and Practice: Guidelines for Reliable, Safe, and Trustworthy Human-Centered AI Systems
Shneiderman B · 2020
Earlier work this paper cites.
In AI we trust? Perceptions about automated decision-making by artificial intelligence
Araujo T, Helberger N, Kruikemeier S, de Vreese CH · 2020
Earlier work this paper cites.
The Relationship between Trust in AI and Trustworthy Machine Learning Technologies
Toreini E, Aitken M, Coopamootoo K, Elliott K, Zelaya CG, van Moorsel A · 2020
Earlier work this paper cites.
Responsible AI—Two Frameworks for Ethical Design Practice
Peters D, Vold K, Robinson D, Calvo RA · 2020
Earlier work this paper cites.
Getting into the engine room: a blueprint to investigate the shadowy steps of AI ethics
Rochel J, Evéquoz F · 2020
Earlier work this paper cites.
The Ethics of AI Ethics: An Evaluation of Guidelines
Hagendorff T · 2020
Earlier work this paper cites.
A Survey on Ethical Principles of AI and Implementations
Zhou J, Chen F, Berry A, Reed M, Zhang S, Savage S · 2020
Earlier work this paper cites.
A non-Discriminatory Approach to Ethical Deep Learning
Tartaglione E, Grangetto M · 2020
Earlier work this paper cites.
The importance of interpretability and visualization in machine learning for applications in medicine and health care
Vellido A · 2020
Earlier work this paper cites.
Interpreting Interpretability: Understanding Data Scientists’ Use of Interpretability Tools for Machine Learning
Kaur H, Nori H, Jenkins S, Caruana R, Wallach H, Wortman Vaughan J · 2020
Earlier work this paper cites.
Machine Learning – The Results Are Not the only Thing that Matters! What About Security, Explainability and Fairness?
Choraś M, Pawlicki M, Puchalski D, Kozik R · 2020
Earlier work this paper cites.
What Do People Really Want When They Say They Want Explainable AI? We Asked 60 Stakeholders
Brennen A · 2020
Earlier work this paper cites.
CERTIFAI: A Common Framework to Provide Explanations and Analyse the Fairness and Robustness of Black-Box Models
Sharma S, Henderson J, Ghosh J · 2020
Earlier work this paper cites.
One Explanation Does Not Fit All
Sokol K, Flach P · 2020
Earlier work this paper cites.
Trustworthy AI Needs Unbiased Dictators!
Abolfazlian K · 2020
Earlier work this paper cites.
Privacy in the Era of 5G, IoT, Big Data and Machine Learning
Bertino E · 2020
Earlier work this paper cites.
Security and Privacy Issues in Deep Learning: A Brief Review
Ha T, Dang TK, Le H, Truong TA · 2020
Earlier work this paper cites.
A review of privacy-preserving techniques for deep learning
Boulemtafes A, Derhab A, Challal Y · 2020
Earlier work this paper cites.
Developing Privacy-preserving AI Systems: The Lessons learned
Chen H, Hussain SU, Boemer F, Stapf E, Sadeghi AR, Koushanfar F, et al · 2020
Earlier work this paper cites.
Privacy-Preserving Machine Learning as a Tool for Secure Personalized Information Services
Sergey Zapechnikov · 2020
Earlier work this paper cites.
Private-kNN: Practical Differential Privacy for Computer Vision
Zhu Y, Yu X, Chandraker M, Wang YX · 2020
Earlier work this paper cites.
A Training Scheme of Deep Neural Networks on Encrypted Data
Yuan L, Shen G · 2020
Earlier work this paper cites.
A novel privacy-preserving speech recognition framework using bidirectional LSTM
Wang Q, Feng C, Xu Y, Zhong H, Sheng VS · 2020
Earlier work this paper cites.
CrossPriv: User Privacy Preservation Model for Cross-Silo Federated Software
Diddee H, Kansra B · 2020
Earlier work this paper cites.
Federated Learning with Gaussian Differential Privacy
Chuanxin Z, Yi S, Degang W · 2020
Earlier work this paper cites.
Federated Learning and Differential Privacy: Software tools analysis, the Sherpa.ai FL framework and methodological guidelines for preserving data privacy
Nuria Rodríguez-Barroso, Goran Stipcich, Daniel Jiménez-López, José Antonio Ruiz-Millán, Eugenio Martínez-Cámara, Gerardo González-Seco, et al · 2020
Earlier work this paper cites.
Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training?
Abuadbba S, Kim K, Kim M, Thapa C, Camtepe SA, Gao Y, et al · 2020
Earlier work this paper cites.
Privacy preservation through facial de-identification with simultaneous emotion preservation
Agarwal A, Chattopadhyay P, Wang L · 2020
Earlier work this paper cites.
Human-in-the-Loop-Aided Privacy-Preserving Scheme for Smart Healthcare
Zhou T, Shen J, He D, Vijayakumar P, Kumar N · 2020
Earlier work this paper cites.
Human-in-the-Loop-Aided Privacy-Preserving Scheme for Smart Healthcare
Zhou T, Shen J, He D, Vijayakumar P, Kumar N · 2020
Earlier work this paper cites.
Information privacy, impact assessment, and the place of ethics*
Charles D Raab · 2020
Earlier work this paper cites.
Beyond Near- and Long-Term: Towards a Clearer Account of Research Priorities in AI Ethics and Society
Prunkl C, Whittlestone J · 2020
Earlier work this paper cites.
Explainability Fact Sheets: A Framework for Systematic Assessment of Explainable Approaches
Sokol K, Flach P · 2020
Earlier work this paper cites.
An Empirical Evaluation of AI Deep Explainable Tools
Hailemariam Y, Yazdinejad A, Parizi RM, Srivastava G, Dehghantanha A · 2020
Earlier work this paper cites.
A Light-Weight Crowdsourcing Aggregation in Privacy-Preserving Federated Learning System
Zhang K, Yiu SM, Hui LCK · 2020
Earlier work this paper cites.
TransNet: Training Privacy-Preserving Neural Network over Transformed Layer
He Q, Yang W, Chen B, Geng Y, Huang L · 2020
Earlier work this paper cites.
XGNN: Towards Model-Level Explanations of Graph Neural Networks
Yuan H, Tang J, Hu X, Ji S · 2020
Earlier work this paper cites.
Available from: https://digital-strategy.ec.europa.eu/en/library/coordinated-plan-artificial-intelligence-2021-review
European Commission. Coordinated Plan on Artificial Intelligence 2021 Review. European Commission.; 2021 · 2021
Earlier work this paper cites.
Available from: https://eur-lex.europa.eu/legal-content/EN/TXT/?qid=1623335154975&uri=CELEX%3A52021PC0206
European Commission. Proposal for a REGULATION OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL LAYING DOWN HARMONISED RULES ON ARTIFICIAL INTELLIGENCE (ARTIFICIAL INTELLIGENCE ACT) AND AMENDING CERTAIN UNION LEGISLATIVE ACTS. European Commission.; 2021 · 2021
Earlier work this paper cites.
Beyond the promise: implementing ethical AI
Eitel-Porter R · 2021
Earlier work this paper cites.
Knowledge-Intensive Language Understanding for Explainable AI
Sheth A, Gaur M, Roy K, Faldu K · 2021
Earlier work this paper cites.
Trustworthy AI
Wing JM · 2021
Earlier work this paper cites.
Trusted Artificial Intelligence: Technique Requirements and Best Practices
Zhang T, Qin Y, Li Q · 2021
Earlier work this paper cites.
Lessons learned from AI ethics principles for future actions
Hickok M · 2021
Earlier work this paper cites.
Ethics as a Service: A Pragmatic Operationalisation of AI Ethics
Morley J, Elhalal A, Garcia F, Kinsey L, Mökander J, Floridi L · 2021
Earlier work this paper cites.
Operationalising AI ethics: how are companies bridging the gap between practice and principles? An exploratory study
Ibáñez JC, Olmeda MV · 2021
Earlier work this paper cites.
AI Ethics: Algorithmic Determinism or Self-Determination? The GPDR Approach
Milossi M, Alexandropoulou-Egyptiadou E, Psannis KE · 2021
Earlier work this paper cites.
Trustworthy AI
Singh R, Vatsa M, Ratha N · 2021
Earlier work this paper cites.
The European way of doing Artificial Intelligence: The state of play implementing Trustworthy AI
Beckert B · 2021
Earlier work this paper cites.
The Sanction of Authority: Promoting Public Trust in AI
Knowles B, Richards JT · 2021
Earlier work this paper cites.
Who Is Included in Human Perceptions of AI?: Trust and Perceived Fairness around Healthcare AI and Cultural Mistrust
Lee MK, Rich K · 2021
Earlier work this paper cites.
AI Trust Score: A User-Centered Approach to Building, Designing, and Measuring the Success of Intelligent Workplace Features
Wang J, Moulden A · 2021
Earlier work this paper cites.
Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in AI
Jacovi A, Marasović A, Miller T, Goldberg Y · 2021
Earlier work this paper cites.
Dual humanness and trust in conversational AI: A person-centered approach
Peng Hu, Yaobin Lu, Yeming (Yale) Gong · 2021
Earlier work this paper cites.
A Survey on the Explainability of Supervised Machine Learning
Burkart N, Huber MF · 2021
Earlier work this paper cites.
Philosophical foundations for digital ethics and AI Ethics: a dignitarian approach
Hanna R, Kazim E · 2021
Earlier work this paper cites.
Socially Responsible AI Algorithms: Issues, Purposes, and Challenges
Cheng L, Varshney KR, Liu H · 2021
Earlier work this paper cites.
A choices framework for the responsible use of AI
Benjamins R · 2021
Earlier work this paper cites.
Ethics-by-design: the next frontier of industrialization
Bourgais A, Ibnouhsein I · 2021
Earlier work this paper cites.
ECCOLA — A method for implementing ethically aligned AI systems
Ville Vakkuri, Kai-Kristian Kemell, Marianna Jantunen, Erika Halme, Pekka Abrahamsson · 2021
Earlier work this paper cites.
Putting AI ethics to work: are the tools fit for purpose?
Ayling J, Chapman A · 2021
Earlier work this paper cites.
Who pays for ethical debt in AI?
Petrozzino C · 2021
Earlier work this paper cites.
Organisational responses to the ethical issues of artificial intelligence
Stahl BC, Antoniou J, Ryan M, Macnish K, Jiya T · 2021
Earlier work this paper cites.
Discussion on Ethical Dilemma Caused by Artificial Intelligence and Countermeasures
Xiaoling P · 2021
Earlier work this paper cites.
The AI ethicist’s dilemma: fighting Big Tech by supporting Big Tech
Sætra HS, Coeckelbergh M, Danaher J · 2021
Earlier work this paper cites.
Towards an ethics of AI in Africa: rule of education
Kiemde SMA, Kora AD · 2021
Earlier work this paper cites.
Ethics and Governance of Artificial Intelligence: Evidence from a Survey of Machine Learning Researchers
Zhang B, Anderljung M, Kahn L, Dreksler N, Horowitz MC, Dafoe A · 2021
Earlier work this paper cites.
Opening the path to ethics in artificial intelligence
Forbes K · 2021
Earlier work this paper cites.
Imagine a More Ethical AI: Using Stories to Develop Teens’ Awareness and Understanding of Artificial Intelligence and its Societal Impacts
Forsyth S, Dalton B, Foster EH, Walsh B, Smilack J, Yeh T · 2021
Earlier work this paper cites.
AI, Explainability and Public Reason: The Argument from the Limitations of the Human Mind
Maclure J · 2021
Earlier work this paper cites.
Notions of explainability and evaluation approaches for explainable artificial intelligence
Giulia Vilone, Luca Longo · 2021
Earlier work this paper cites.
XAI Tools in the Public Sector: A Case Study on Predicting Combined Sewer Overflows
Maltbie N, Niu N, van Doren M, Johnson R · 2021
Earlier work this paper cites.
A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems
Mohseni S, Zarei N, Ragan ED · 2021
Earlier work this paper cites.
How Can I Choose an Explainer? An Application-Grounded Evaluation of Post-Hoc Explanations
Jesus S, Belém C, Balayan V, Bento J, Saleiro P, Bizarro P, et al · 2021
Earlier work this paper cites.
Expanding Explainability: Towards Social Transparency in AI Systems
Ehsan U, Liao QV, Muller M, Riedl MO, Weisz JD · 2021
Earlier work this paper cites.
Capturing the Trends, Applications, Issues, and Potential Strategies of Designing Transparent AI Agents
Sun L, Li Z, Zhang Y, Liu Y, Lou S, Zhou Z · 2021
Earlier work this paper cites.
Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and Their Needs
Suresh H, Gomez SR, Nam KK, Satyanarayan A · 2021
Earlier work this paper cites.
Differential Privacy Defenses and Sampling Attacks for Membership Inference
Rahimian S, Orekondy T, Fritz M · 2021
Cited alongside, same era.
Differential Privacy: The Pursuit of Protections by Default
Guevara M, Desfontaines D, Waldo J, Coatta T · 2021
Cited alongside, same era.
Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings
Suriyakumar VM, Papernot N, Goldenberg A, Ghassemi M · 2021
Cited alongside, same era.
Prescriptive analytics with differential privacy
Harikumar H, Rana S, Gupta S, Nguyen T, Kaimal R, Venkatesh S · 2021
Cited alongside, same era.
Differentially Private Deep Learning with Iterative Gradient Descent Optimization
Ding X, Chen L, Zhou P, Jiang W, Jin H · 2021
Cited alongside, same era.
An efficient approach for privacy preserving decentralized deep learning models based on secure multi-party computation
Software engineering for responsible AI: an empirical study and operationalised patterns
Lu Q, Zhu L, Xu X, Whittle J, Douglas D, Sanderson C · 2022
Later among the works it cites.
Toward Involving End-users in Interactive Human-in-the-loop AI Fairness
Nakao Y, Stumpf S, Ahmed S, Naseer A, Strappelli L · 2022
Later among the works it cites.
iHealth: The ethics of artificial intelligence and big data in mental healthcare
Rubeis G · 2022
Later among the works it cites.
Algorithmic fairness datasets: the story so far
Fabris A, Messina S, Silvello G, Susto GA · 2022
Later among the works it cites.
Artificial intelligence ethics has a black box problem
Bélisle-Pipon JC · 2022
Later among the works it cites.
Community-in-the-loop: towards pluralistic value creation in AI, or—why AI needs business ethics
Häußermann JJ, Lütge C · 2022
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Anh-Tu Tran, The-Dung Luong, Jessada Karnjana, Van-Nam Huynh · 2021
Cited alongside, same era.
When Machine Learning Meets Privacy: A Survey and Outlook
Liu B, Ding M, Shaham S, Rahayu W, Farokhi F, Lin Z · 2021
Cited alongside, same era.
Federated Learning-Based Privacy-Preserving and Security: Survey
Yang M, He Y, Qiao J · 2021
Cited alongside, same era.
Privacy-Preserving Federated Deep Learning for Wearable IoT-Based Biomedical Monitoring
Can YS, Ersoy C · 2021
Cited alongside, same era.
A Federated Parallel Data Platform for Trustworthy AI
Chen L, Zhang W, Xu L, Zeng X, Lu Q, Zhao H, et al · 2021
Cited alongside, same era.
SAFELearn: Secure Aggregation for private FEderated Learning
Fereidooni H, Marchal S, Miettinen M, Mirhoseini A, Möllering H, Nguyen TD, et al · 2021
Cited alongside, same era.
Efficient, Private and Robust Federated Learning
Hao M, Li H, Xu G, Chen H, Zhang T · 2021
Cited alongside, same era.
Later among the works it cites.
Confucius, cyberpunk and Mr. Science: comparing AI ethics principles between China and the EU
Fung P, Etienne H · 2022
Later among the works it cites.
Explainability as fig leaf? An exploration of experts’ ethical expectations towards machine learning in psychiatry
Starke G, Schmidt B, De Clercq E, Elger BS · 2022
Later among the works it cites.
From computer ethics and the ethics of AI towards an ethics of digital ecosystems
Stahl BC · 2022
Later among the works it cites.
From the ground truth up: doing AI ethics from practice to principles
Brusseau J · 2022
Later among the works it cites.
From the ground up: developing a practical ethical methodology for integrating AI into industry
Anderson MM, Fort K · 2022
Later among the works it cites.
Immune moral models? Pro-social rule breaking as a moral enhancement approach for ethical AI
Ramanayake R · 2022
Later among the works it cites.
Is AI recruiting (un)ethical? A human rights perspective on the use of AI for hiring
Hunkenschroer AL, Kriebitz A · 2022
Later among the works it cites.
Recommender systems for mental health apps: advantages and ethical challenges
Valentine L, D’Alfonso S, Lederman R · 2022
Later among the works it cites.
Reexamining computer ethics in light of AI systems and AI regulation
Jacobs M, Simon J · 2022
Later among the works it cites.
The future of AI in our hands? To what extent are we as individuals morally responsible for guiding the development of AI in a desirable direction?
Persson E, Hedlund M · 2022
Later among the works it cites.
Towards Explainability for AI Fairness
Zhou J, Chen F, Holzinger A · 2022
Later among the works it cites.
Explainable AI
Storey VC, Lukyanenko R, Maass W, Parsons J · 2022
Later among the works it cites.
Explainable machine learning practices: opening another black box for reliable medical AI
Ratti E, Graves M · 2022
Later among the works it cites.
Explainable, trustworthy, and ethical machine learning for healthcare: A survey
Rasheed K, Qayyum A, Ghaly M, Al-Fuqaha A, Razi A, Qadir J · 2022
Later among the works it cites.
Explaining deep neural networks: A survey on the global interpretation methods
Saleem R, Yuan B, Kurugollu F, Anjum A, Liu L · 2022
Later among the works it cites.
Knowledge graphs as tools for explainable machine learning: A survey
Tiddi I, Schlobach S · 2022
Later among the works it cites.
Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond
Yang G, Ye Q, Xia J · 2022
Later among the works it cites.
Explainable AI for Healthcare 5.0: Opportunities and Challenges
Saraswat D, Bhattacharya P, Verma A, Prasad VK, Tanwar S, Sharma G, et al · 2022
Later among the works it cites.
Explainable artificial intelligence: a comprehensive review
Minh D, Wang HX, Li YF, Nguyen TN · 2022
Later among the works it cites.
Debiased-CAM to mitigate image perturbations with faithful visual explanations of machine learning
Zhang W, Dimiccoli M, Lim BY · 2022
Later among the works it cites.
Exploration into the Explainability of Neural Network Models for Power Side-Channel Analysis
Golder A, Bhat A, Raychowdhury A · 2022
Later among the works it cites.
Investigating Explainability of Generative AI for Code through Scenario-based Design
Sun J, Liao QV, Muller M, Agarwal M, Houde S, Talamadupula K, et al · 2022
Later among the works it cites.
Model Explanations with Differential Privacy
Patel N, Shokri R, Zick Y · 2022
Later among the works it cites.
Explainable AI for Industry 4.0: Semantic Representation of Deep Learning Models
Terziyan V, Vitko O · 2022
Later among the works it cites.
Knowledge graph-based rich and confidentiality preserving Explainable Artificial Intelligence (XAI)
Rožanec JM, Fortuna B, Mladenić D · 2022
Later among the works it cites.
Explaining Deep Graph Networks via Input Perturbation
Bacciu D, Numeroso D · 2022
Later among the works it cites.
On Black-Box Explanation for Face Verification
Mery D, Morris B · 2022
Later among the works it cites.
Explaining predictions and attacks in federated learning via random forests
Haffar R, Sánchez D, Domingo-Ferrer J · 2022
Later among the works it cites.
Agree to Disagree: When Deep Learning Models With Identical Architectures Produce Distinct Explanations
Watson M, Shiekh Hasan BA, Moubayed NA · 2022
Later among the works it cites.
How Good is your Explanation? Algorithmic Stability Measures to Assess the Quality of Explanations for Deep Neural Networks
Fel T, Vigouroux D, Cadene R, Serre T · 2022
Later among the works it cites.
Using human-in-the-loop and explainable AI to envisage new future work practices
Tsiakas K, Murray-Rust D · 2022
Later among the works it cites.
A manifesto on explainability for artificial intelligence in medicine
Combi C, Amico B, Bellazzi R, Holzinger A, Moore JH, Zitnik M, et al · 2022
Later among the works it cites.
X-MIR: EXplainable Medical Image Retrieval
Hu B, Vasu B, Hoogs A · 2022
Later among the works it cites.
Black is the new orange: how to determine AI liability
Padovan PH, Martins CM, Reed C · 2022
Later among the works it cites.
Adversarial Robustness is Not Enough: Practical Limitations for Securing Facial Authentication
Joos S, Van hamme T, Preuveneers D, Joosen W · 2022
Later among the works it cites.
An Empirical Evaluation of Adversarial Examples Defences, Combinations and Robustness Scores
Jankovic A, Mayer R · 2022
Later among the works it cites.
What Does it Mean for a Language Model to Preserve Privacy?
Brown H, Lee K, Mireshghallah F, Shokri R, Tramèr F · 2022
Later among the works it cites.
Adversarial attacks on graph-level embedding methods: a case study
Giordano M, Maddalena L, Manzo M, Guarracino MR · 2022
Later among the works it cites.
Privacy-Preserving Detection of Poisoning Attacks in Federated Learning
Muhr T, Zhang W · 2022
Later among the works it cites.
ShieldFL: Mitigating Model Poisoning Attacks in Privacy-Preserving Federated Learning
Ma Z, Ma J, Miao Y, Li Y, Deng RH · 2022
Later among the works it cites.
How to keep text private? A systematic review of deep learning methods for privacy-preserving natural language processing
Sousa S, Kern R · 2022
Later among the works it cites.
Visual privacy attacks and defenses in deep learning: a survey
Zhang G, Liu B, Zhu T, Zhou A, Zhou W · 2022
Later among the works it cites.
Add noise to remove noise: Local differential privacy for feature selection
Alishahi M, Moghtadaiee V, Navidan H · 2022
Later among the works it cites.
Deep Learning Classification of Fetal Cardiotocography Data with Differential Privacy
Lal AK, Karthikeyan S · 2022
Later among the works it cites.
Differential Privacy Preservation in Robust Continual Learning
Hassanpour A, Moradikia M, Yang B, Abdelhadi A, Busch C, Fierrez J · 2022
Later among the works it cites.
A Differential Approach for Data and Classification Service-Based Privacy-Preserving Machine Learning Model in Cloud Environment
Gupta R, Singh AK · 2022
Later among the works it cites.
A two-phase random forest with differential privacy
Liu J, Li X, Wei Q, Liu S, Liu Z, Wang J · 2022
Later among the works it cites.
Correlated Differential Privacy of Multiparty Data Release in Machine Learning
Zhao JZ, Wang XW, Mao KM, Huang CX, Su YK, Li YC · 2022
Later among the works it cites.
Differentially private multivariate time series forecasting of aggregated human mobility with deep learning: Input or gradient perturbation?
Arcolezi HH, Couchot JF, Renaud D, Al Bouna B, Xiao X · 2022
Later among the works it cites.
Privacy-Preserving Fair Learning of Support Vector Machine with Homomorphic Encryption
Park S, Byun J, Lee J · 2022
Later among the works it cites.
Efficient and Privacy-Preserving Logistic Regression Scheme based on Leveled Fully Homomorphic Encryption
Liu C, Jiang ZL, Zhao X, Chen Q, Fang J, He D, et al · 2022
Later among the works it cites.
Efficient homomorphic encryption framework for privacy-preserving regression
Byun J, Park S, Choi Y, Lee J · 2022
Later among the works it cites.
Federated learning and privacy
Bonawitz K, Kairouz P, Mcmahan B, Ramage D · 2022
Later among the works it cites.
Federated Learning for Healthcare: Systematic Review and Architecture Proposal
Antunes RS, André da Costa C, Küderle A, Yari IA, Eskofier B · 2022
Later among the works it cites.
A Review of Medical Federated Learning: Applications in Oncology and Cancer Research
Chowdhury A, Kassem H, Padoy N, Umeton R, Karargyris A · 2022
Later among the works it cites.
Auto-weighted Robust Federated Learning with Corrupted Data Sources
Li S, Ngai E, Ye F, Voigt T · 2022
Later among the works it cites.
CloudyFL: a cloudlet-based federated learning framework for sensing user behavior using wearable devices
Gong Q, Ruan H, Chen Y, Su X · 2022
Later among the works it cites.
Cross-silo federated learning based decision trees
Kalloori S, Klingler S · 2022
Later among the works it cites.
FedNKD: A Dependable Federated Learning Using Fine-tuned Random Noise and Knowledge Distillation
Zhu S, Qi Q, Zhuang Z, Wang J, Sun H, Liao J · 2022
Later among the works it cites.
FLARE: Defending Federated Learning against Model Poisoning Attacks via Latent Space Representations
Wang N, Xiao Y, Chen Y, Hu Y, Lou W, Hou YT · 2022
Later among the works it cites.
Blockchain Empowered Federated Learning for Data Sharing Incentive Mechanism
Wang Z, Yan B, Dong A · 2022
Later among the works it cites.
Decentralized Federated Learning for Nonintrusive Load Monitoring in Smart Energy Communities
Giuseppi A, Manfredi S, Menegatti D, Pietrabissa A, Poli C · 2022
Later among the works it cites.
Towards Trustworthy AI: Blockchain-based Architecture Design for Accountability and Fairness of Federated Learning Systems
Lo SK, Liu Y, Lu Q, Wang C, Xu X, Paik HY, et al · 2022
Later among the works it cites.
Trusted Decentralized Federated Learning
Gholami A, Torkzaban N, Baras JS · 2022
Later among the works it cites.
Trustworthy Federated Learning via Blockchain
Yang Z, Shi Y, Zhou Y, Wang Z, Yang K · 2022
Later among the works it cites.
When Collaborative Federated Learning Meets Blockchain to Preserve Privacy in Healthcare
Abou El Houda Z, Hafid AS, Khoukhi L, Brik B · 2022
Later among the works it cites.
VFL-R: a novel framework for multi-party in vertical federated learning
Li J, Yan T, Ren P · 2022
Later among the works it cites.
Privacy-preserving federated neural network learning for disease-associated cell classification
Sav S, Bossuat JP, Troncoso-Pastoriza JR, Claassen M, Hubaux JP · 2022
Later among the works it cites.
Homomorphic Encryption and Federated Learning based Privacy-Preserving CNN Training: COVID-19 Detection Use-Case
Wibawa F, Catak FO, Kuzlu M, Sarp S, Cali U · 2022
Later among the works it cites.
Data Privacy Protection Sharing Strategy Based on Consortium Blockchain and Federated Learning
Feng X, Chen L · 2022
Later among the works it cites.
Privacy Risk Assessment of Training Data in Machine Learning
Bai Y, Fan M, Li Y, Xie C · 2022
Later among the works it cites.
Privacy vs Accuracy Trade-Off in Privacy Aware Face Recognition in Smart Systems
Abbasi W, Mori P, Saracino A, Frascolla V · 2022
Later among the works it cites.
Privacy-Preserving Case-Based Explanations: Enabling Visual Interpretability by Protecting Privacy
Montenegro H, Silva W, Gaudio A, Fredrikson M, Smailagic A, Cardoso JS · 2022
Later among the works it cites.
Privacy-Preserving Classification Scheme Based on Support Vector Machine
Mao Q, Chen Y, Duan P, Zhang B, Hong Z, Wang B · 2022
Later among the works it cites.
PrivPAS: A real time Privacy-Preserving AI System and applied ethics
Harichandana BSS, Agarwal V, Ghosh S, Ramena G, Kumar S, Raja BRK · 2022
Later among the works it cites.
Sphinx: Enabling Privacy-Preserving Online Learning over the Cloud
Tian H, Zeng C, Ren Z, Chai D, Zhang J, Chen K, et al · 2022
Later among the works it cites.
Towards Personalized Federated Learning
Tan AZ, Yu H, Cui L, Yang Q · 2022
Later among the works it cites.
Trustworthy Artificial Intelligence: A Review
Kaur D, Uslu S, Rittichier KJ, Durresi A · 2023
Later among the works it cites.
Federated Learning for Smart Healthcare: A Survey
Nguyen DC, Pham QV, Pathirana PN, Ding M, Seneviratne A, Lin Z, et al · 2023
Later among the works it cites.
PVD-FL: A Privacy-Preserving and Verifiable Decentralized Federated Learning Framework
Zhao J, Zhu H, Wang F, Lu R, Liu Z, Li H · 2059
Closest in time.
Designing Up with Value-Sensitive Design: Building a Field Guide for Ethical ML Development
Boyd K · 2069
Closest in time.