Adding and multiplying invariant random matrices Faculty of Physics and Applied Computer Science AGH University of Science and Technology Krakow, Poland

Source URL: ptcp16.complexity-coventry.org

NIST SP 800-90A, Recommendation for Random Number Generations Using Deterministic Random Bit Generations

Source URL: projectbullrun.org

Random Reflections on Day One of the UN Summit By Rene Raya, ASPBAE Policy Analyst 25 September 2015, New York Security was tight during the Papal address at the Opening Plenary of the UN Summit, so I missed these events

Source URL: aspbae.org

Limits on Sparse Support Recovery via Linear Sketching with Random Expander Matrices Jonathan Scarlett and Volkan Cevher Laboratory for Information and Inference Systems (LIONS) École Polytechnique Fédérale de Lausann

Source URL: jmlr.org

A model and architecture for pseudo-random generation with applications to /dev/random Boaz Barak∗ Department of Computer Science Princeton University

Source URL: eprint.iacr.org

An algorithmic framework for obtaining lower bounds for random Ramsey problems Rajko Nenadov1 Yury Person2

Source URL: arxiv.org

Mark Burgin*, UCLA, Los Angeles, CA 90095, and Alan C. Krinik, California State Polytechnic University, Pomona, CAWhat to do with Random Variables that don’t have Expectations. Preliminary report.

Source URL: jointmathematicsmeetings.org

Journal of Machine Learning Research1822 Submitted 9/07; Published 8/08 Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks

Source URL: www.jmlr.org

Incorporating Vector Space Similarity in Random Walk Inference over Knowledge Bases Matt Gardner Carnegie Mellon University

Source URL: emnlp2014.org

On the Relationship between Sum-Product Networks and Bayesian Networks Han Zhao HAN . ZHAO @ UWATERLOO . CA Mazen Melibari MMELIBAR @ UWATERLOO . CA

Source URL: jmlr.org

• Graphical models
• Statistical models
• Probability theory
• Bayesian network
• Networks
• Variable elimination
• Markov random field