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  Browse All Reviews > Mathematics Of Computing (G) > Probability And Statistics (G.3)  
 
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  1-10 of 422 Reviews about "Probability And Statistics (G.3)": Date Reviewed
  Distributional reinforcement learning
Bellemare M., Dabney W., Rowland M., MIT Press, Cambridge, Massachucetts, 2023. 384 pp.  Type: Book (0262048019)

Rarely does a book introduce a new field of study at the intersection of computer science, deep reinforcement learning (RL), probability theory, statistics, and applied math. In their work at Google DeepMind, the authors applied technologies like ...

Feb 5 2024
  Parallel-and-stream accelerator for computationally fast supervised learning
Hector E., Luo L., Song P. Computational Statistics & Data Analysis 177(1): 1-12, 2022.  Type: Article

Large enterprises with massive amounts of data require reliable and efficient algorithms for exploring and forecasting trends in available supplies, user purchases, and advertisements. The scalability of the MapReduce approach is advantageous for ...

Feb 20 2023
  Excel 2019 for physical sciences statistics: a guide to solving practical problems (2nd ed.)
Quirk T., Quirk M., Horton H., Springer International Publishing, Cham, Switzerland, 2021. 264 pp.  Type: Book (978-3-030632-37-3)

This self-teaching volume belongs to a long series of similar volumes by Thomas Quirk (the main author) about the basic uses of Microsoft Excel spreadsheet software for simple statistics. This second edition covers the 2019 version of Excel, while...

Oct 31 2022
   Bringing Bayesian models to life
Hooten M., Hefley T., CRC Press, Boca Raton, FL, 2019. 573 pp.  Type: Book (978-0-367198-48-0)

We are used to classical statistics, yet in many important contemporary applications, such as the estimation of parameters in machine learning, a second branch of statistics based on Bayesian methods is very attractive. Therefore, a bo...

Aug 23 2022
   Statistics for data scientists: an introduction to probability, statistics, and data analysis
Kaptein M., van den Heuvel E., Springer International Publishing, Cham, Switzerland, 2022. 348 pp.  Type: Book (978-3-030105-30-3)

One would hope that professionals calling themselves data scientists would have extensive training in both statistical theory and practice. Yet current data analytics curricula, while naturally including at least one general statistics...

Jul 7 2022
  A First Look at Stochastic Processes
Rosenthal J., WORLD SCIENTIFIC, Singapore, 2020. 202 pp.  Type: Book (978-9-811208-97-3)

Although intended as a textbook, Rosenthal’s A first look at stochastic processes is not quite there. However, it is still a very interesting and useful text with a good account of challenging problems. While the autho...

Jul 1 2022
   Quantum techniques in stochastic mechanics
Baez J., Biamonte J., WORLD SCIENTIFIC, Singapore, Singapore, 2018. 263 pp.  Type: Book (978-9-813226-93-7)

In an increasingly specialized world, it is a rare pleasure when a book can build compelling and useful connections among widely different disciplines. This volume offers such a treat, merging physics (the mathematics of quantum field ...

Feb 12 2021
  Learning and decision-making from rank data
Xia L., Morgan&Claypool Publishers, San Rafael, CA, 2019. 160 pp.  Type: Book (978-1-681734-40-8)

Due to the proliferation of Internet devices and connections, data is generated at an extreme speed. Right now, zettabytes of data are generated daily. How to make meaning out of mostly unstructured data is very difficult. Among these ...

Dec 23 2020
  Nonhomogeneous place-dependent Markov chains, unsynchronised AIMD, and optimisation
Wirth F., Stüdli S., Yu J., Corless M., Shorten R. Journal of the ACM 66(4): 1-37, 2019.  Type: Article

The transmission control protocol (TCP) that underpins most Internet traffic has a simple yet intuitively beautiful algorithm for congestion control. Every connection will gradually ramp up the bandwidth it uses until congestion occurs...

Oct 19 2020
   A domain theory for statistical probabilistic programming
Vákár M., Kammar O., Staton S. Proceedings of the ACM on Programming Languages 3(POPL): 1-29, 2019.  Type: Article

On the one hand, a statistical programming language is similar to a traditional programming language, but with libraries providing statistical functions. Examples are Mathematica, MATLAB, and the omnipresent R. On the other hand, proba...

Aug 6 2020
 
 
 
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