Bayesian Basics, Explained

@machinelearnbot

Editor's note: The following is an interview with Columbia University Professor Andrew Gelman conducted by Marketing scientist Kevin Gray, in which Gelman spells out the ABCs of Bayesian statistics. Kevin Gray: Most marketing researchers have heard of Bayesian statistics but know little about it. Can you briefly explain in layperson's terms what it is and how it differs from the'ordinary' statistics most of us learned in college? Andrew Gelman: Bayesian statistics uses the mathematical rules of probability to combines data with "prior information" to give inferences which (if the model being used is correct) are more precise than would be obtained by either source of information alone. Classical statistical methods avoid prior distributions.


Bayesian Basics, Explained

#artificialintelligence

Editor's note: The following is an interview with Columbia University Professor Andrew Gelman conducted by Marketing scientist Kevin Gray, in which Gelman spells out the ABCs of Bayesian statistics. Andrew Gelman: Bayesian statistics uses the mathematical rules of probability to combines data with "prior information" to give inferences which (if the model being used is correct) are more precise than would be obtained by either source of information alone. Classical statistical methods avoid prior distributions. In classical statistics, you might include in your model a predictor (for example), or you might exclude it, or you might pool it as part of some larger set of predictors in order to get a more stable estimate. These are pretty much your only choices.


Network Science: Understanding the Internal Organization of Complex Systems (Invited Talk)

AAAI Conferences

The Center for Complex Network Research (CCNR), directed by Professor Barabasi, has a simple objective: think networks. The center's research focuses on how networks emerge, what they look like, and how they evolve; and how networks impact on understanding of complex systems. To understand networks, CCNR's research has developed to rather unexpected areas. Certain studies include the topology of the www - showing that webpages are on average 19 clicks form each other; complex cellular network inside the cell-looking at both metabolic and genetic networks; the Internet's Achilles' Heel. The center's researchers have even ventured to study how actors are connected in Hollywood.


Professor Stephen Hawking warns of rogue robot rebellion evolving faster than humans

Daily Mail - Science & tech

A sinister threat is brewing deep inside the technology laboratories of Silicon Valley, according to Professor Stephen Hawking. Artificial Intelligence, disguised as helpful digital assistants and self-driving vehicles, is gaining a foothold, and it could one day spell the end for mankind. The world-renowned professor has warned robots could evolve faster than humans and their goals will be unpredictable. Professor Stephen Hawking (pictured) claimed AI would be difficult to stop if the appropriate safeguards are not in place. During a talk in Cannes, Google's chairman Eric Schmidt said AI will be developed for the benefit of humanity and there will be systems in place in case anything goes awry.


Artificial intelligence could 'evolve faster than the human race'

#artificialintelligence

A sinister threat is brewing deep inside the technology laboratories of Silicon Valley, according to Professor Stephen Hawking. Artificial Intelligence, disguised as helpful digital assistants and self-driving vehicles, is gaining a foothold, and it could one day spell the end for mankind. The world-renowned professor has warned robots could evolve faster than humans and their goals will be unpredictable. Professor Stephen Hawking (pictured) claimed AI would be difficult to stop if the appropriate safeguards are not in place. During a talk in Cannes, Google's chairman Eric Schmidt said AI will be developed for the benefit of humanity and there will be systems in place in case anything goes awry.