David H. Bailey mainly focuses on Algorithm, Parallel computing, Computation, Floating point and Extended precision. His studies deal with areas such as Transcendental function, Number theory, Arithmetic, Experimental mathematics and Subroutine as well as Algorithm. His Parallel computing study incorporates themes from Fast Fourier transform, Latency and Scalability.
His Computation research integrates issues from Software, Computer engineering and Code. The various areas that David H. Bailey examines in his Extended precision study include Arbitrary-precision arithmetic and Computational science. His biological study spans a wide range of topics, including Applied research, Set and Parallel processing.
The scientist’s investigation covers issues in Computation, Experimental mathematics, Parallel computing, Sharpe ratio and Econometrics. His Computation study also includes fields such as
His work carried out in the field of Parallel computing brings together such families of science as Fast Fourier transform and Set. His Sharpe ratio research is multidisciplinary, relying on both Multiple comparisons problem and Selection bias. His Arbitrary-precision arithmetic research entails a greater understanding of Algorithm.
His primary scientific interests are in Sharpe ratio, Overfitting, Econometrics, Investment strategy and Computation. The study incorporates disciplines such as Multiple comparisons problem, Modern portfolio theory and Selection bias in addition to Sharpe ratio. His work in the fields of Econometrics, such as Econometric methods, overlaps with other areas such as Market forecast.
His research integrates issues of Numerical integration, Algebra, Arithmetic and Pure mathematics in his study of Computation. A large part of his Arithmetic studies is devoted to Arbitrary-precision arithmetic. His Experimental mathematics research includes elements of Theoretical computer science and Calculus.
David H. Bailey mainly focuses on Overfitting, Investment strategy, Sharpe ratio, Econometrics and Context. His work often combines Overfitting and Investment management studies. Many of his Investment strategy research pursuits overlap with Finance, Small number and Out of sample.
David H. Bailey has researched Econometrics in several fields, including Selection bias and Portfolio. His Portfolio research is multidisciplinary, incorporating elements of Market data, Nonparametric statistics and Regression. His Context research spans across into areas like Minifloat, Mathematical physics, Arbitrary-precision arithmetic, Arithmetic and Empirical data.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
The Nas Parallel Benchmarks
D.H. Bailey;E. Barszcz;J.T. Barton;D.S. Browning.
ieee international conference on high performance computing data and analytics (1991)
IEEE Standard for Floating-Point Arithmetic
Dan Zuras;Mike Cowlishaw;Alex Aiken;Matthew Applegate.
IEEE Std 754-2008 (2008)
On the rapid computation of various polylogarithmic constants
David Bailey;Peter Borwein;Simon Plouffe.
Mathematics of Computation (1997)
FFTs in external or hierarchical memory
D. H. Bailey.
The Journal of Supercomputing (1990)
Experimentation in mathematics : computational paths to discovery
Jonathan M. Borwein;David H. Bailey;Roland Girgensohn.
The fractional Fourier transform and applications
David H. Bailey;Paul N. Swarztrauber.
Siam Review (1991)
Algorithms for quad-double precision floating point arithmetic
Y. Hida;X.S. Li;D.H. Bailey.
symposium on computer arithmetic (2001)
Precimonious: tuning assistant for floating-point precision
Cindy Rubio-González;Cuong Nguyen;Hong Diep Nguyen;James Demmel.
ieee international conference on high performance computing data and analytics (2013)
Design, implementation and testing of extended and mixed precision BLAS
Xiaoye S. Li;James W. Demmel;David H. Bailey;Greg Henry.
ACM Transactions on Mathematical Software (2002)
Enhancing reproducibility for computational methods.
Victoria Stodden;Marcia McNutt;David H. Bailey;Ewa Deelman.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: