About Samuel Horváth Samuel Horváth Ph.D. Student, Statistics machine learning optimization statistics big data Samuel Horváth is a Ph.D. candidate at Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST), studying under the supervision of Professor Peter Richtarik in his research group. Education and Early Career Samuel studied Financial Mathematics at Comenius University in Bratislava, Slovakia and obtained his bachelor in 2017. Then, he joined the MS/PhD program in Statistics and Optimization at KAUST in 2017. In 2018, he had an internship (Machine Learning Intern) at Exponea for 3 months. Research Interest His research interest include Optimization for Big Data Articles Related News October 2019 Less chat leads to more work for machine learning 2 min read · Wed, Oct 16 2019 News machine learning Computer science Deep analysis of the way information is shared among parallel computations increases efficiency to accelerate machine learning at scale.
Less chat leads to more work for machine learning 2 min read · Wed, Oct 16 2019 News machine learning Computer science Deep analysis of the way information is shared among parallel computations increases efficiency to accelerate machine learning at scale.
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