Brian Bullins
About
Brian Bullins has authored 15 papers that have received a total of 130 indexed citations.
This includes 13 papers in Artificial Intelligence, 10 papers in Computational Mechanics and 6 papers in Computational Theory and Mathematics. The topics of these papers are Stochastic Gradient Optimization Techniques (11 papers), Sparse and Compressive Sensing Techniques (10 papers) and Machine Learning and Algorithms (5 papers). Brian Bullins is often cited by papers focused on Stochastic Gradient Optimization Techniques (11 papers), Sparse and Compressive Sensing Techniques (10 papers) and Machine Learning and Algorithms (5 papers) and collaborates with scholars based in United States, United Kingdom and France. Brian Bullins's co-authors include Elad Hazan, Naman Agarwal, Tengyu Ma, Coralia Cartis and Zeyuan Allen-Zhu and has published in prestigious journals such as Mathematical Programming, Journal of Machine Learning Research and SIAM Journal on Optimization
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