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Artem Artemev

PhD - Machine Learning at Imperial College London

Artem Artemev is a PhD candidate in Machine Learning at Imperial College London, currently in his second year of research.12 He is supervised by Mark van der Wilk, an Associate Professor in Machine Learning at the same institution.2

Artemev's research focuses on machine learning theory and approximate Bayesian inference, with a particular interest in non-parametric machine learning methods like Gaussian processes.1 His recent work addresses the scalability of Gaussian processes while maintaining their predictive properties when approximations are involved.1

Prior to starting his PhD, Artemev worked as a Machine Learning Researcher and Engineer for startup companies.1 His current research involves developing an XLA compiler extension that adjusts the computational dataflow representation of algorithms according to user-specified memory limits.1 This work aims to improve the efficiency of memory-intensive algorithms in machine learning, allowing them to run at a larger scale on single devices.1

Artemev has presented his research on "Memory Safe Computations with XLA Compiler" at academic seminars, demonstrating the practical applications of his work in improving the performance of k-nearest neighbor and sparse Gaussian process regression methods.1

Highlights

Research Group - Mark van der Wilk
Artem Artemev - Memory Safe Computations with XLA Compiler
Artem Artemev - Memory Safe Computations with XLA Compiler

Related Questions

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Artem Artemev
Artem Artemev, photo 1
Artem Artemev, photo 2
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Location

Cambridge, United Kingdom