Abstract: A delay-constrained scheduling problem for point-to-point communication is considered: a packet of B bits must be transmitted by a hard deadline of T slots over a time-varying channel. The ...

Russell (Rust Scientific Library) helps develop high-performance computations involving linear algebra, sparse linear systems, numerical mathematics (continuation), differential equations, statistics, ...

Chemistry, mathematics and physics are central to our understanding of nature. Physics explores the fundamental laws of mechanics, electromagnetism, quantum mechanics and relativity. Chemistry studies ...

Linear algebra is central to many algorithms in engineering, science, and machine learning; hence, accelerating it would have tremendous economic impact. Quantum computing has been proposed for this ...

Introduction: Compared to Genome-Wide Association Studies (GWAS) for common variants, single-marker association analysis for rare variants is underpowered. Set-based association analyses for rare ...

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This paper explores the mathematics behind optimal portfolio construction when relative utility and risk are considered together in a general sense. I derive the ...

Understanding human memory has been a long-standing problem in various scientific disciplines. Early works focused on characterizing human memory using small-scale controlled experiments and these ...

Partial differential equations (PDEs) are among the most ubiquitous tools used in modeling problems in nature. However, solving high-dimensional PDEs has been notoriously difficult due to the “curse ...

The key idea behind the probabilistic framework to machine learning is that learning can be thought of as inferring plausible models to explain observed data. A machine can use such models to make ...