Check computer science papers: citations, claims and retractions

A Potentially Realizable Quantum Computer

Lloyd, S. (1993) · Science

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 649

Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology

Tellez, D., Litjens, G., Bándi, P., Bulten, W., Bokhorst, J.-M., Ciompi, F., & van der Laak, J. (2019) · Medical Image Analysis

AI in cancer detectionDigital Imaging for Blood Diseases

Cited by 649

An artificial immune network for multimodal function optimization

de Castro, L. N., & Timmis, J. (2003) · Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)

Artificial Immune Systems ApplicationsMetaheuristic Optimization Algorithms Research

Cited by 648

The Complexity of the Local Hamiltonian Problem

Kempe, J., Kitaev, A., & Regev, O. (2006) · SIAM Journal on Computing

Quantum Computing Algorithms and ArchitectureComplexity and Algorithms in Graphs

Cited by 648

The Hidden Vulnerability of Distributed Learning in Byzantium

Mhamdi, E. M. E., Guerraoui, R., & Rouault, S. (2018) · arXiv

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 648

Some Difficulties of Learning to Program

Du Boulay, B. (1986) · Journal of Educational Computing Research

Teaching and Learning ProgrammingLogic, programming, and type systems

Cited by 648

RSVM: Reduced Support Vector Machines

Lee, Y.-J., & Mangasarian, O. L. (2001) · Proceedings of the 2001 SIAM International Conference on Data Mining

Stochastic Gradient Optimization TechniquesMachine Learning and Data Classification

Cited by 647

Assessing computational thinking: A systematic review of empirical studies

Tang, X., Yin, Y., Lin, Q., Hadad, R., & Zhai, X. (2020) · Computers & Education

Teaching and Learning ProgrammingEducation and Critical Thinking Development

Cited by 647

Exploring the potential of using an AI language model for automated essay scoring

Mizumoto, A., & Eguchi, M. (2023) · Research Methods in Applied Linguistics

Natural Language Processing TechniquesEFL/ESL Teaching and Learning

Cited by 647

Quantum Algorithm for Systems of Linear Equations with Exponentially Improved Dependence on Precision

Childs, A. M., Kothari, R., & Somma, R. D. (2017) · SIAM Journal on Computing

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 646

Fairness in Machine Learning: A Survey

Caton, S., & Haas, C. (2020) · arXiv

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 646

A Survey on quantum computing technology

Gyongyosi, L., & Imre, S. (2019) · Computer Science Review

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 646

Fairness in machine learning: A survey

Caton, S., & Haas, C. (2024) · ACM Computing Surveys

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 646

How bodies matter: five themes for interaction design

Klemmer, S. R., Hartmann, B., & Takayama, L. (2006) · Proceedings of the 6th conference on Designing Interactive systems

Innovative Human-Technology InteractionInteractive and Immersive Displays

Cited by 645

A secure federated transfer learning framework

Liu, Y., Kang, Y., Xing, C., Chen, T., & Yang, Q. (2020) · IEEE Intelligent Systems

Privacy-Preserving Technologies in DataDomain Adaptation and Few-Shot Learning

Cited by 645

Fairness Constraints: Mechanisms for Fair Classification

Zafar, M. B., Valera, I., Rodriguez, M. G., & Gummadi, K. P. (2015) · arXiv

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 645

A Blockchain-Based Decentralized Federated Learning Framework with Committee Consensus

Li, Y., Chen, C., Liu, N., Huang, H., Zheng, Z., & Yan, Q. (2021) · IEEE Network

Privacy-Preserving Technologies in DataBlockchain Technology Applications and Security

Cited by 645

Coyote optimization algorithm: A new metaheuristic for global optimization problems

Pierezan, J., & Dos Santos Coelho, L. (2018) · 2018 IEEE Congress on Evolutionary Computation (CEC)

Metaheuristic Optimization Algorithms ResearchAdvanced Optimization Algorithms Research

Cited by 645

Inferring Networks of Substitutable and Complementary Products

McAuley, J., Pandey, R., & Leskovec, J. (2015) · Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Recommender Systems and TechniquesComplex Network Analysis Techniques

Cited by 645

Website Fingerprinting at Internet Scale

Panchenko, A., Lanze, F., Zinnen, A., Henze, M., Pennekamp, J., Wehrle, K., & Engel, T. (2016) · Proceedings 2016 Network and Distributed System Security Symposium

Internet Traffic Analysis and Secure E-votingPrivacy, Security, and Data Protection

Cited by 645

Secure Federated Transfer Learning

Liu, Y., Kang, Y., Xing, C., Chen, T., & Yang, Q. (2018) · arXiv

Privacy-Preserving Technologies in DataDomain Adaptation and Few-Shot Learning

Cited by 645

Ethical Machine Learning in Healthcare

Chen, I. Y., Pierson, E., Rose, S., Joshi, S., Ferryman, K., & Ghassemi, M. (2021) · Annual Review of Biomedical Data Science

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 645

Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond

Yang, J., Jin, H., Tang, R., Han, X., Feng, Q., Jiang, H., Yin, B., & Hu, X. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 644

Harnessing the power of llms in practice: a survey on chatGPT and beyond

Yang, J., Jin, H., Tang, R., Han, X., Feng, Q., Jiang, H., Zhong, S., Yin, B., & Hu, X. (2024) · ACM Transactions on Knowledge Discovery from Data

Topic ModelingNatural Language Processing Techniques

Cited by 644