Check computer science papers: citations, claims and retractions

Fast SVM training algorithm with decomposition on very large data sets

Dong, J.-X., Krzyzak, A., & Suen, C. Y. (2005) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Stochastic Gradient Optimization TechniquesMachine Learning and ELM

Cited by 230

Combining billing codes, clinical notes, and medications from electronic health records provides superior phenotyping performance

Wei, W.-Q., Teixeira, P. L., Mo, H., Cronin, R. M., Warner, J. L., & Denny, J. C. (2016) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareMedical Coding and Health Information

Cited by 230

For You, or For"You"?: Everyday LGBTQ+ Encounters with TikTok

Simpson, E., & Semaan, B. (2021) · Proceedings of the ACM on Human-Computer Interaction

Ethics and Social Impacts of AILGBTQ Health, Identity, and Policy

Cited by 230

Topological pattern recognition for point cloud data

Carlsson, G. (2014) · Acta Numerica

Topological and Geometric Data AnalysisHomotopy and Cohomology in Algebraic Topology

Cited by 230

Towards End-to-End Text Spotting with Convolutional Recurrent Neural Networks

Li, H., Wang, P., & Shen, C. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV)

Handwritten Text Recognition TechniquesVehicle License Plate Recognition

Cited by 230

Affective state estimation for human–robot Interaction

Kulic, D., & Croft, E. A. (2007) · IEEE Transactions on Robotics

Emotion and Mood RecognitionSocial Robot Interaction and HRI

Cited by 230

Clingo = ASP + Control: Preliminary Report

Gebser, M., Kaminski, R., Kaufmann, B., & Schaub, T. (2014) · arXiv

Logic, Reasoning, and KnowledgeConstraint Satisfaction and Optimization

Cited by 230

The Penguin Has Entered the Building: The Commercialization of Open Source Software Products

Fosfuri, A., Giarratana, M. S., & Luzzi, A. (2008) · Organization Science

Open Source Software InnovationsIntellectual Property and Patents

Cited by 229

Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward

Lo Piano, S. (2020) · Humanities and Social Sciences Communications

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 229

A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning

Fraccaro, M., Kamronn, S., Paquet, U., & Winther, O. (2017) · arXiv

Generative Adversarial Networks and Image SynthesisGaussian Processes and Bayesian Inference

Cited by 229

Measurement of Quality of Experience of Video-on-Demand Services: A Survey

Juluri, P., Tamarapalli, V., & Medhi, D. (2016) · IEEE Communications Surveys & Tutorials

Image and Video Quality AssessmentNetwork Traffic and Congestion Control

Cited by 229

The Effects of Levels of Immersion on Memory and Presence in Virtual Environments: A Reality Centered Approach

Mania, K., & Chalmers, A. (2001) · CyberPsychology & Behavior

Virtual Reality Applications and ImpactsSimulation and Modeling Applications

Cited by 229

Fuzz4ALL: Universal Fuzzing with Large Language Models

Xia, C. S., Paltenghi, M., Le Tian, J., Pradel, M., & Zhang, L. (2024) · Proceedings of the IEEE/ACM 46th International Conference on Software Engineering

Software Testing and Debugging TechniquesSoftware Engineering Research

Cited by 229

Privacy Risks of Securing Machine Learning Models against Adversarial Examples

Song, L., Shokri, R., & Mittal, P. (2019) · Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 229

The probability of causal conditionals

Over, D. E., Hadjichristidis, C., Evans, J. S. B. T., Handley, S. J., & Sloman, S. A. (2007) · Cognitive Psychology

Logic, Reasoning, and KnowledgeSyntax, Semantics, Linguistic Variation

Cited by 229

Delving into deep imbalanced regression

Yang, Y., Zha, K., Chen, Y.-C., Wang, H., & Katabi, D. (2021) · arXiv

Imbalanced Data Classification TechniquesMachine Learning and Data Classification

Cited by 229

Stackelberg games for adversarial prediction problems

Brückner, M., & Scheffer, T. (2011) · Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining

Spam and Phishing DetectionAdversarial Robustness in Machine Learning

Cited by 229

A computer-aided environment for generating multiple-choice test items

MITKOV, R., AN HA, L., & KARAMANIS, N. (2006) · Natural Language Engineering

Natural Language Processing TechniquesAdvanced Text Analysis Techniques

Cited by 229

Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling

Luo, B., Xiao, W., Wang, S., Huang, J., & Tassiulas, L. (2022) · IEEE INFOCOM 2022 - IEEE Conference on Computer Communications

Privacy-Preserving Technologies in DataStochastic Gradient Optimization Techniques

Cited by 229

Decoupled extended Kalman filter training of feedforward layered networks

Puskorius, G. V., & Feldkamp, L. A. (2002) · IJCNN-91-Seattle International Joint Conference on Neural Networks

Neural Networks and ApplicationsMachine Learning and ELM

Cited by 229

Measuring the Effects of Data Parallelism on Neural Network Training

Shallue, C. J., Lee, J., Antognini, J., Sohl-Dickstein, J., Frostig, R., & Dahl, G. E. (2018) · arXiv

Stochastic Gradient Optimization TechniquesNeural Networks and Applications

Cited by 229

Optimal multimodal fusion for multimedia data analysis

Wu, Y., Chang, E. Y., Chang, K. C.-C., & Smith, J. R. (2004) · Proceedings of the 12th annual ACM international conference on Multimedia

Multimodal Machine Learning ApplicationsVideo Analysis and Summarization

Cited by 229

Machine learning model to predict mental health crises from electronic health records

Garriga, R., Mas, J., Abraha, S., Nolan, J., Harrison, O., Tadros, G., & Matic, A. (2022) · Nature Medicine

Machine Learning in HealthcareMental Health via Writing

Cited by 229

ASVspoof: The Automatic Speaker Verification Spoofing and Countermeasures Challenge

Wu, Z., Yamagishi, J., Kinnunen, T., Hanilci, C., Sahidullah, M., Sizov, A., Evans, N., Todisco, M., & Delgado, H. (2017) · IEEE Journal of Selected Topics in Signal Processing

Speech Recognition and SynthesisBiometric Identification and Security

Cited by 229