NSF Workshop on Algorithms In The Field: Request Ideas

NSF Workshop on Algorithms In The Field (W8F) will assemble CSists from networking, databases, social networks, data mining, machine learning, graphics/vision/geometry/robotics and those from algorithms and theoretical computer science. It is a wider collection than you'd find in most meetings yet small enough to discuss or even debate.

Many of you are native experts in 8F. Many of you have first hand experience of being algorithms researchers and working with others on a common challenge or vice versa. Also, many of you have thought about frustrations and triumphs, in collaborations that involve algorithms/theory researchers.

This is a call for help. Please email any issues you think we should explore; any questions you would like any particular community to address or any pair of communities to debate, or for a panel to ponder; any ideas for how to organize this workshop, etc. Here are some potential examples (disclaimer: this list is limited by my background and lack of imagination):

• [Technical] Is recommendation only a machine learning problem? What problem would be most interesting to database/networking/machine learning/ folks if we could do a smoothed analysis? Is there a networking analysis for which streaming algorithm is the bottleneck? What problems in database engine is a bottleneck for which databases will be willing to live with approximation? Is there a uber version of nearest neighbors of interest to vision/machine learning/data mining? Is there a structural theory of social behavior that can be captured by graph theory? Can we prove via reductions that problems in these areas are related to each other (at a deeper level than by formulating common data structure/graph/scheduling problems)? Is there an applied area where scheduling is the bottleneck? Are there key problems in massive data analysis that needs efficient MapReduce algorithms? If algorithmic complexity was not the bottleneck, what will be main problems in vision, data mining, machine learning systems?
  
• [Organization] If there is an annual conf on 8F, what advice will you provide? Besides developing metrics, what questions about 8F can we that will be helpful to the Kanellakis awards committee. Propose new grand challenges in 8F that requires algorithms folks and others to work together to accomplish.
  
• [Education] How should we train students in 8F? What algorithms area do researchers in databases, networking, machine learning, vision, graphics etc. wish they (or their students) knew better? What format will be a summer school take that aims at teaching algorithms/theory students about the various fields? What will be a "field trip" in CS (akin to say in Biology)?