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Probabilistic Computation (F.1.2...)
Conditioning in probabilistic programming
Olmedo F., Gretz F., Jansen N., Kaminski B., Katoen J., Mciver A. ACM Transactions on Programming Languages and Systems 40(1): 1-50, 2018. Type: Article
Machine learning, possibly contrary to popular belief, is not just about endless variations of neural networks. There is also a thriving subculture of probabilistic programming based on Bayesian principles. A large advantage of the lat...
Jun 13 2018
Discrete probability models and methods: probability on graphs and trees, Markov chains and random fields, entropy and coding
Brémaud P., Springer International Publishing, New York, NY, 2017. 559 pp. Type: Book (978-3-319434-75-9)
Due to advances in both theory and practice, there has been a recent explosion in courses on network science and data science. These demand a solid background in probabilistic methods....
Feb 21 2018
Semantics of probabilistic processes: an operational approach
Deng Y., Springer Publishing Company, Incorporated, New York, NY, 2015. 249 pp. Type: Book (978-3-662451-97-7)
This is a good resource for understanding issues related to the semantic foundations of concurrent systems. The author especially examines bisimulation semantics and testing semantics....
Oct 20 2015
Majority-based reversible logic gates
Yang G., Hung W., Song X., Perkowski M. Theoretical Computer Science 334(1-3): 259-274, 2005. Type: Article
Yang et al. investigate the construction of reversible logic gates without constants. The key area of application is quantum computing. The basic idea of reversible computing is to avoid destroying bits. This has the physical correlate...
Nov 28 2005
Probability and computing: randomized algorithms and probabilistic analysis
Mitzenmacher M., Upfal E., Cambridge University Press, New York, NY, 2005. 368 pp. Type: Book (9780521835404)
Randomization and probabilistic techniques are important in many disciplines, especially computer science. Often, randomized algorithms are the simplest, the fastest, or both. They are applied in a number of domains, such as combinator...
Sep 30 2005
First course on fuzzy theory and applications
Lee K., SpringerVerlag, 2004. Type: Book (9783540229889)
Fuzzy systems handle imprecise concepts. Using fuzzy sets and fuzzy logic, one can build expert systems and controllers that have the advantages of being easy to understand, and of requiring less processing power than comparable neural...
Feb 7 2005
Explorations in quantum computing
Williams C. (ed), Clearwater S. (ed), TELOS, Santa Clara, CA, 1998. Type: Book (9780387947686)
Quantum computing is distinguished from classical computing in the same way that quantum mechanics is different from classical mechanics. The fundamental assumption in classical mechanics is that the properties of a dynamical system ar...
Jun 1 1998
A time-randomness trade-off for oblivious routing
Peleg D., Upfal E. SIAM Journal on Computing 19(2): 256-266, 1990. Type: Article
Understanding the role of randomness in the theory of computation is rapidly becoming one of the central, challenging problems facing computer scientists. The ultimate goal of research in this area is to develop a clear theory that exp...
Aug 1 1991
Probabilistic inductive inference
Pitt L. Journal of the ACM 36(2): 383-433, 1989. Type: Article
This lengthy paper considers inductive inference, especially by probabilistic machines. An inductive inference machine is an algorithmic device that attempts to infer rules from examples, where a rule is any recursive function
Sep 1 1989
Discrete random process stabilization
Lorenc A., Lapins J. Information and Control 58(1-3): 1-18, 1984. Type: Article
Davis  represented the structural synthesis of a stochastic finite-state machine in terms of some relations between finite Markov chains and deterministic finite-state machines. Earlier, Dvoretzky and Wolfowitz  proposed a method...
May 1 1986
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