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Lakshmivarahan, S.
University of Oklahoma
Norman, Oklahoma
 
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- 10 of 22 reviews

   
   Social big data analytics: practices, techniques, and applications
Abu-Salih B., Wongthongtham P., Zhu D., Yan Chan K., Rudra A., Springer International Publishing, Cham, Switzerland, 2021. 228 pp.  Type: Book (978-3-030686-50-5)

Thanks to the advances in wireless sensor communication, large-scale storage, and computing technologies, those who can afford to be in one or more of the available platforms--the Internet, WhatsApp, or Twitter, to name a few--are connec...

Nov 8 2022  
  Mathematical foundations of big data analytics
Shikhman V., Müller D., Springer International Publishing, New York, NY, 2021. 288 pp.  Type: Book (978-3-662625-20-0), Reviews: (1 of 2)

Mathematical foundations of big data analytics is a very welcome and timely addition to the growing area of big data analytics. The authors develop--and strictly follow in each of the nine chapters--a template ...

Jul 5 2021  
   Computational methods for deep learning: theoretic, practice and applications
Yan W., Springer International Publishing, Cham, Switzerland, 2021. 211 pp.  Type: Book (978-3-030610-80-7), Reviews: (3 of 3)

Computational methods for deep learning is written for the typical second-year graduate student at a US university, working in this area for his/her PhD-level dissertation research on the application of various manifestations of...

Apr 23 2021  
   Computational methods for deep learning: theoretic, practice and applications
Yan W., Springer International Publishing, Cham, Switzerland, 2021. 211 pp.  Type: Book (978-3-030610-80-7), Reviews: (1 of 3)

Computational methods for deep learning is written for the typical second-year graduate student at a US university, working in this area for his/her PhD-level dissertation research on the application of various manifestations of...

Apr 23 2021  
   Computational methods for deep learning: theoretic, practice and applications
Yan W., Springer International Publishing, Cham, Switzerland, 2021. 211 pp.  Type: Book (978-3-030610-80-7), Reviews: (2 of 3)

Computational methods for deep learning is written for the typical second-year graduate student at a US university, working in this area for his/her PhD-level dissertation research on the application of various manifestations of...

Apr 23 2021  
  Number theory for computing
Yan S., Springer-Verlag New York, Inc., Secaucus, NJ, 2002. 445 pp.  Type: Book (9783540430728)

This is an excellent and timely addition to the growing body of literature on computational number theory. It has a very pleasant mix of basic theory, numerous examples that supplement the theory, and computational insights that natur...

Oct 29 2002  
  Macro-Star Networks: Efficient Low-Degree Alternatives to Star Graphs
Yeh C., Varvarigos E. IEEE Transactions on Parallel and Distributed Systems 9(10): 987-1003, 1998.  Type: Article

This paper introduces an extension of star graphs, called macro-star graphs, based on an interesting combinatorial paradigm. The authors show that the graphs in this class have sublogarithmic diameter, which is asymptotically optimal. ...

May 1 1999  
  Foundations of algorithms
Neapolitan R., Naimipour K., D. C. Heath and Company, Lexington, MA, 1996.  Type: Book (9780669352986)

By its very nature, the study of algorithms is quite mathematical. While there may not be any agreement about the prerequisites for a first course in algorithms at the advanced undergraduate level, I believe the usual calculus sequence...

Mar 1 1998  
  A random NP-complete problem for inversion of 2D cellular automata
Durand B. Theoretical Computer Science 148(1): 19-32, 1995.  Type: Article

Cellular automata (CA) have been used to model the evolution of complex systems with local interactions. A CA consists of a large number of simple cells, each interacting with a small number of neighbors specified in advance. The probl...

Aug 1 1996  
  Network solution
Kłs A., Aitchison P., Ellis Horwood, Upper Saddle River, NJ, 1993.  Type: Book (9780136135890)

The state space approach to the analysis of linear electrical networks, using tools from matrix theory, is emphasized in this advanced book. It describes the principles that are basic to the development of algorithms and the associated...

Apr 1 1995  
 
 
 
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