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Boian S. Alexandrov
Also published under:Boian S. Alexandro, B. S. Alexandrov, B. Alexandrov, Boian Alexandrov
Affiliation
Advanced Research in Cyber Systems, Los Alamos National Laboratory, Los Alamos, USA
Topic
Non-negative Matrix Factorization,Positive Matrix,Matrix Factorization,Automatic Determination,Column Vector,Large Datasets,Scientific Literature,Sparse Datasets,Tensor Decomposition,Topic Modeling,Adoption Of Machine Learning,Anomaly Detection,Batch Size,Benign Samples,Bias Term,Black-box Attacks,Citation Network,Client Participation,Cloud Data,Clustering-based Methods,Cognitive System,Collaborative Filtering,Communication Rounds,Complex Systems,Computational Biology,Computer Vision,Consensus Method,Contralateral,Count Data,Critical Infrastructure,Cybersecurity Knowledge,Data Block,Data Transfer,Dataset In This Paper,Decoy Selection,Decoy Set,Deep Learning,Density Score,Diagonal Matrix,Differential Privacy,Difficulty Level,Dirichlet Process,Distributed Algorithm,Distribution Of Categories,Distribution Of Services,Distribution System,Easy Cases,Energy Function,Estimation Of Model Accuracy,Family Classification,
Biography
Boian S. Alexandrov received the M.S. degree in theoretical physics, the Ph.D. degree in nuclear engineering, and the second Ph.D. degree in computational biophysics. He is currently a Senior Scientist at the Theoretical Division, Los Alamos National Laboratory. He is specialized in big data analytics, nonnegative matrix and tensor factorization, unsupervised learning, and latent feature extraction.