2023 4th International Conference on Frontiers of Artificial Intelligence and SGtatistics (CFAIS 2023)

CFAIS 2023


Artificial Intelligence Probability & Statistics with Applications



2023 4th International Conference on Frontiers of Artificial Intelligence and Statistics (CFAIS 2023)--Ei Compendex & Scopus—Call for paper 



August 18-20, 2023Nanjing, ChinaWebsite: www.cfais.org



 



★CFAIS 2023 welcomes researchers, engineers, scientists and industry professionals to an open forum where advances in the field of Artificial Intelligence and Statistics can be shared and examined. The conference is an ideal platform for keeping up with advances and changes to a consistently morphing field. Leading researchers and industry experts from around the globe will be presenting the latest studies through papers and oral presentations. 



 



★Publication and Indexing



Accepted and presented papers of CFAIS 2023 will be published in the digital conference proceedings which will submitted to Ei Compendex, Scopus, CPCI, Google Scholar and other major databases for index.



Excellent papers will be recommended to be published in the journal.



 



★Keynote Speakers



Prof. Weifeng Gao——Xidian University, China



 



 



★Program Preview/ Program at a glance



August 18: Registration + Icebreaker Reception



August 19: Opening Ceremony+ KN Speech+ Technical Sessions



August 20: Technical Sessions+ Half day tour/Lab tours



 



★Paper Submission



PDF version submit via CMT: https://cmt3.research.microsoft.com/CFAIS2023



 



★CONTACT US



Ms. Riva H. W. Wong



Email: info@cfais.org   



Website: www.cfais.org



 



Topics of Interest



Approximate inference



Bayesian learning



Business process intelligence



Causal models



Classification



Clustering



Density estimation



Federated learning



Gaussian processes



Generalization and regularization



Graphical models



High-performance computation



Intelligent optimization



Kernel and spectral methods



Large-scale optimization algorithm



Logic and probability



Manifolds learning



Multi-agent systems



Non-Bayesian models and estimation



Nonparametric models



No-regret learning



Optimization for deep learning



Privacy-preserving learning



Reinforcement learning



Software and applications of artificial intelligence



Sparsity and compressed sensing



Statistical and computational learning theory



Statistical optimization



Structural learning and prediction



Unsupervised and semi-supervised learning