Since the last Around the blogs in 80 summer hours, the flat line activity of the Summer on the interwebs seems to be over. First of all, we had quite a few implementation made available by their authors.
When mentioning those subjects: Streaming Data Mining and the GraphLab and GraphChi group on LinkedIn, it occurred to me that, for my own sake, I needed to do a synthesis of what we are currently seeing. I applied to give a TEDxParis talk but they declined, unbeknownst to me the theme of the meeting was 2030 so I decided to provide a glimpse of August 25th, 2030 based on what we know, no crystal ball here just applying what we have seen so far and doing a little of interpolation.. Here are part 1 and 2 of the material on which the talk would have been based on:
Talking about TED, here is a TED Talk by Ramesh Raskar on Imaging at a trillion frames per second. The random bit of the week is this finding on The First Programmable Robot You've Never Heard of.
The activity on the blogs has regained some steam:
Dirk provided a nice overview of some of the talks at ISMP:
- ISMP first day
- ISMP, second day
- ISMP over – non-convex and non-smooth minimization, l^1 and l^p
- ISMP – inverse problems with uniform noise and TV does not preserve edges
- ISMP – alternatingly projecting on non-convex sets and demixing by convex optimization
Bob tells us about EUSIPCO
Laurent features a call for papers on Time-frequency analysis and applications
Emmanuel explains his Radio silence. Lots of good stuff coming up.
- Airlines on time performance dataset
- Collaborative filtering with GraphChi
- On convergence of Gaussian BP
- Steffen Rendle - libFM
- 80-20 rule - or collaborative filtering in practice
- A Workshop on Topology and Machine Learning
- Robins and Wasserman Respond to a Nobel Prize Winner
- What Every Statistician Should Know About Computer Science (and Vice-Versa)
- P-values Gone Wild and Multiscale Madness
Rich let us know that Rice Founds E-Learning Center
Andrej has set up a nifty Academic Countdown
Christian reminds us about the Bayes by the Bay meeting
Greg features Juha Vierinen's jitter project, GNU Ionospheric Tomography Receiver
Yannick let is know about a group meeting on CS and medical imagery in France.
Carter intends on building some Haskell version of some of the advanced Matrix factorization algorithms.
John lists the Patterns for research in machine learning
David has some advice on 7 Habits of the Open Scientist #3: Pre-publication dissemination of research
Finally, if you thought Nature was in the business of high quality and high impact papers, you might rethink that in light of this Guest Post: Terry Rudolph on Nature versus Nurture
Image Credit: NASA/JPL-Caltech/MSSS, Focusing the 100-millimeter Mastcam, layered buttes of Mount Sharp,
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