A Ubiquity symposium is an organized debate around a proposition or point of view. It is a means to explore a complex issue from multiple perspectives. An early example of a symposium on teaching computer science appeared in Communications of the ACM (December 1989).
To organize a symposium, please read our guidelines.
Ubiquity Symposium: Evolutionary Computation and the Processes of Life
Table of Contents
1. Evolutionary Computation and the Processes of Life, Opening Statement, by Mark Burgin and Eugene Eberbach
2. Life Lessons Taught by Simulated Evolution, by Hans-Paul Schwefel
3. The Essence of Evolutionary Computation, by Xin Yao
4. On the Role of Evolutionary Models in Computing, by Max Garzon
5. Evolutionary Computation as a Direction in Nature-inspired Computing, by Hongwei Mo
6. The Emperor is Naked: Evolutionary Algorithms for Real-World Applications, by Zbigniew Michalewicz
7. Darwinian Software Engineering, by Moshe Sipper
8. Evolutionary Computation and Evolutionary Game Theory, by David Fogel
9. Evolutionary Computation in the Physical World, by Lukas Sekanina
10. Some Aspects of Computation Essential to Evolution and Life, by Hector Zenil and James Marshall
11. Information, Biological and Evolutionary Computing, by Walter Riofrio
14. Perspectives and Reality of Evolutionary Computation, Closing Statement, by Mark Burgin and Eugene Eberbach
Ubiquity Symposium: The Science in Computer Science
Table of Contents
1. The Science In Computer Science Opening Statement, by Peter Denning
2. Computer Science Revisited, Vinton Cerf
4. Broadening CS Enrollments: An interview with Jan Cuny, by Richard Snodgrass
5. How to Talk About Science: Five Essential Insights, Shawn Carlson
6. The Sixteen Character Traits of Science, by Philip Yaffe
7. Why You Should Choose Math in High School, by Espen Andersen
8. On Experimental Algorithmics: An Interview with Catherine Mcgeoch and Bernard Moret,by Richard Snodgrass
10. An Interview with Mark Guzdial, by Peter Denning
11. An Interview with David Alderson: In search of the real network science, by Peter Denning
12. Natural Computation, by Erol Gelenbe
13. Where’s the Science in Software Engineering?, by Walter Tichy
14. The Computing Sciences and STEM Education, by Paul Rosenbloom
15. Unplugging Computer Science to Find the Science, by Tim Bell
16. Closing Statement, by Richard Snodgrass and Peter Denning
When Good Machine Learning Leads to Bad Security: Big Data (Ubiquity symposium)
by Tegjyot Singh Sethi, Mehmed Kantardzic
While machine learning has proven to be promising in several application domains, our understanding of its behavior and limitations is still in its nascent stages. One such domain is that of cybersecurity, where machine learning models are replacing traditional rule based systems, owing to their ability to generalize and deal with large scale attacks which are not seen before. However, the naive transfer of machine learning principles to the domain of security needs to be taken with caution. Machine learning was not designed with security in mind and as such is prone to adversarial manipulation and reverse engineering. While most data based learning models rely on a static assumption of the world, the security landscape is one that is especially dynamic, with an ongoing never ending arms race between the system designer and the attackers. Any solution designed for such a domain needs to take into account an active adversary and needs to evolve over time, in the face of emerging threats. We term this as the "Dynamic Adversarial Mining" problem, and this paper provides motivation and foundation for this new interdisciplinary area of research, at the crossroads of machine learning, cybersecurity, and streaming data mining.
Developing an Open Source 'Big Data' Cognitive Computing Platform: Big Data (Ubiquity symposium)
by Michael Kowolenko, Mladen A. Vouk
March 2018The ability to leverage diverse data types requires a robust and dynamic approach to systems design. The needs of a data scientist are as varied as the questions being explored. ...
High Performance Synthetic Information Environments
An integrating architecture in the age of pervasive data and computing: Big Data (Ubiquity symposium)
by Christopher L. Barrett, Jeffrey Johnson, Madhav Marathe
March 2018The complexities of social and technological policy domains, such as the economy, the environment, and public health, present challenges that require a new approach to modeling and decision-making. ...
Technology and Business Challenges of Big Data in the Digital Economy: Big Data (Ubiquity symposium)
by Dave Penkler
January 2018The early digital economy during the dot-com days of internet commerce successfully faced its first big data challenges of click-stream analysis with map-reduce technology. Since then the digital economy has ...
Big Data for Social Science Research: Big Data (Ubiquity symposium)
by Mark Birkin
January 2018Academic studies exploiting novel data sources are scarce. Typically, data is generated by commercial businesses or government organizations with no mandate and little motivation to share their assets with academic ...