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One of my favorite workshops from the last five years was the IITK Workshop on Algorithms for Data Streams (see here for a report) back in 2006. This was also the meeting that resulted in the oft-cited Kanpur open problems list.
Well, I’m back in Kanpur for the unofficial sequel, the IITK Workshop on Algorithms for Processing Massive Data Sets and, so far, the talks, the organization, and the food (!) have been just as good. The workshop is principally organized by Sumit Ganguly. Thanks Sumit!
I hope to write more when time permits but, for now, please check out the schedule where videos and slides will soon be posted. Also, Krzysztof Onak and I are working on compiling another open problems document but let me get back to that.
The accepted list from STACS has just been posted. Streaming papers that caught my eye include:
- AMS Without 4-Wise Independence on Product Domains [Ostrovsky, Braverman]
- Improved Approximation Guarantees for Weighted Matching in the Semi-Streaming Model [Epstein, Levin, Mestre, Segev]
- Continuous Monitoring of Distributed Data Streams over a Time-based Sliding Window [Chan, Lam, Lee, Ting]
On the topic of conferences, if you head across to Vancouver/Whistler tomorrow, you can hear about some new stream results at NIPS and then go skiing. Does it get better than that?
- Streaming k-means approximation [Ailon, Jaiswal, Monteleoni]
- Streaming Pointwise Mutual Information [Van Durme, Lall]
On an entirely different topic, are you a smart, enthusiastic undergraduate with an interest in doing some exciting research in data streams (or algorithms in general) for your Ph.D? Perhaps you should apply to UMass. Just a thought…