Santa Fe Institute

Events News

Science On Screen continues May 8 with Simon DeDeo and 'Sneakers'
April 30, 2013 -

The popular Science On Screen series returns to Santa Fe Wednesday evening, May 8, with Simon DeDeo and the 1992 cult hacker film Sneakers.

Video: How social media might help you survive the next big disaster
March 25, 2013 -

SFI's 2013 Community Lecture series debuted March 14 with UC-Boulder's Leysia Palen describing how victims, observers, and “citizen-responders” are using modern technology to participate in disaster response. Watch ...

Climate scientists James Hansen, at SFI, calls for energy sources to foot their 'true' costs
Feb. 22, 2013 -

Speaking at SFI yesterday, noted climate scientist James Hansen told an overflow crowd that efforts to stem climate change will be ineffectual as long as fossil fuels remain the cheapest ...

SFI's successful crowdfunding campaign will help scientists study indigenous people
Dec. 14, 2012 -

SFI's crowdfunding campaign has reached its goal. The resulting research will help scientists preserve the threatened landscapes on which indigenous human groups depend. 

The Gods Must Be Crazy with Murray Gell-Mann
Dec. 13, 2012 -

The 2012 Science On Screen series in Santa Fe wrapped up December 13 to a full house, with "The Gods Must Be Crazy" and Murray Gell-Mann's distinctive insight and ...

More News

Multi-Information Source Optimization

Working Group

November 29, 2012 - November 30, 2012
Noyce Conference Room

The field of optimization concerns iterative procedures for finding the x that extremizes a function f(x). Often an optimization problem comes with several information sources concerning the relation between x and f(x) that one can sample at each iteration, each source incurring a different sampling cost. Multi-Information Source Optimization (MISO) is the problem of how to optimally choose among such a set of information sources during an overall optimization algorithm. The key issue is how to combine information from all those sources while trading off the value of each source's samples and the cost of generating them.

    One example of MISO is where the information sources are different computational simulators of the climate’s dynamics, with varying accuracy and varying cost (in terms of how fast they run). In this example the MISO goal is to optimally exploit those simulators to find the climate parameters that give the best fit to observational data, subject to a penalty on total cost incurred. Other kinds of MISO applications involve finding optimal designs of engineered systems. Examples include how best to use a set of simulators of an exascale computer to find the optimal architecture of such a computer, and how best to a set of condensed matter simulators together with laboratory experiments to find the material that optimizes some desired physical properties of the material.

    MISO is related to existing work on multi-fidelity optimization, multi-disciplinary optimization, active learning, semi-supervised machine learning, adaptive experimental design, and several other bodies of work. However it extends substantially beyond any of them.

    This working group will be a gathering of researchers to discuss approaches to multi-sampler optimization and plan potential collaborations for joint work on it.

SFI Host: David Wolpert

  • * SFI community lectures are free, open, & accessible to the public.
  • * Seminars & colloquia are geared for scientists but free & open to the interested public.
  • * All other SFI events are by invitation only.
  • * Note: We are unable to accommodate members of the public for SFI's limited lunch service; you're welcome to bring your own.