Tag Archives: computer science

Hello from the IPAM Workshop on Privacy for Biomedical Data

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I just arrived in LA for the IPAM Workshop on Algorithmic Challenges in Protecting Privacy for Biomedical Data. I co-organized this workshop with Cynthia Dwork, James Zou, and Sriram Sankararaman and it is (conveniently) before the semester starts and (inconveniently) overlapping with the MIT Mystery Hunt. The workshop has a really diverse set of speakers so to get everyone on the same page and anchor the discussion, we have 5 tutorial speakers and a few sessions or shorter talks. The hope is that these tutorials (which are on the first two days of the workshop) will give people some “common language” to discuss research problems.

The other big change we made to the standard workshop schedule was to put in time for “breakout groups” to have smaller discussions focused on identifying the key fundamental problems that need to be addressed when thinking about privacy and biomedical data. Because of the diversity of viewpoints among participants, it seems a tall order to generate new research collaborations out of attending talks and going to lunch. But if we can, as a group, identify what the mathematical problems are (and maybe even why they are hard), this can help identify the areas of common interest.

I think of these as falling into a few different categories.

  • Questions about demarcation. Can we formalize (mathematically) the privacy objective in different types of data sets/computations? Can we use these to categorize different types of problems?
  • Metrics. How do we formulate the privacy-utility tradeoffs for different problems? What is the right measure of performance? What (if anything) do we lose in guaranteeing privacy?
  • Possibility/impossibility. Algorithms which can guarantee privacy and utility are great, but on the flip side we should try to identify when privacy might be impossible to guarantee. This would have implications for higher-level questions about system architectures and policy.
  • Domain-specific questions. In some cases all of the setup is established: we want to compute function F on dataset D under differential privacy and the question is to find algorithms with optimal utility for fixed privacy loss or vice versa. Still, identifying those questions and writing them down would be a great outcome.

In addition to all of this, there is a student poster session, a welcome reception, and lunches. It’s going to be a packed 3 days, and although I will miss the very end of it, I am excited to learn a lot from the participants.

Postdoctoral Associate at DIMACS

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DIMACS, the Center for Discrete Mathematics and Theoretical Computer Science, invites applications for various postdoctoral associate positions for 2017-18. Applicants should be recent Ph.D.’s with interest in DIMACS areas, such as computer science, discrete mathematics, statistics, physics, operations research, and their applications. There are four positions available:

  1. a one-year postdoctoral associateship investigating modeling of anomaly detection in multi-layer networks,
  2. a two-year associateship in collaboration with the Institute for Advanced Study (IAS) in Princeton, NJ emphasizing theoretical computer science and discrete mathematics,
  3. a position associated with the Simons Collaboration on Algorithms and Geometry which also emphasizes theoretical computer science and discrete mathematics and could be hosted at Rutgers/DIMACS,
  4. a two-year associateship in theoretical machine learning in the Department of Computer Science at Rutgers.

See the DIMACS website for application information.

Applications have various deadlines, beginning December 1, 2016. See website for details.
DIMACS Center, Rutgers University, 96 Frelinghuysen Road, Piscataway, NJ 08854-8018;
Tel: 848-445-5928; Email: postdoc at dimacs.rutgers.edu. DIMACS is an EO/AA employer.

Signal boost: Postdoc in Privacy at Penn State

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Sofya Raskhodnikova and Adam Smith are looking to fill a postdoc position at Penn State for a multi-year project on privacy, streaming and learning.

Qualifications: Ph.D., with expertise in the theoretical foundations of at least one of the research areas (algorithms, machine learning and statistics, data privacy). Willingness to work on a cross-disciplinary project.

More about the project leaders: Sofya Raskhodnikova, Adam Smith.

Duration and compensation: At least one year, renewable. Start date is
negotiable, though we slightly prefer candidates starting fall 2015. Salary is competitive.

Applicants should email a CV, short research statement and list of references directly to the project leaders ({asmith,sofya}@cse.psu.edu) with “postdoc” in the subject line.

Location: The university is located in the beautiful college town of
State College in the center of Pennsylvania. The State College area has 130,000 inhabitants and offers a wide variety of cultural and outdoor recreational activities. The university offers outstanding events from collegiate sporting events to fine arts productions. Many major population centers on the east coast (New York, Philadelphia, Pittsburgh, Washington D.C., Baltimore) are only a few hours’ drive away and convenient air services to several major hubs are operated by three major airlines out of State College.

Penn State is an equal opportunity employer. We encourage applications from underrepresented minorities.

Linkage

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Some old links I meant to post a while back but still may be of interest to some…

I prefer my okra less slimy, but to each their own.

Via Erin, A tour of the old homes of the Mission.

Also via Erin, Women and Crosswords and Autofill.

A statistician rails against computer science’s intellectual practices.

Nobel Laureate Randy Schekman is boycotting Nature, Science, and Cell. Retraction Watch is skeptical.

Linkage

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I occasionally enjoy Thai cooking, so I appreciated some of the comments made by Andy Ricker.

I recently learned about India’s Clean Currency Policy which went into effect this year. I still have some money (in an unpacked box, probably) from my trip this last fall, and I wonder if any of it will be still usable when I go to SPCOM 2014 this year. That sounded a bit crazy to me though, further investigation indicates that an internal circular leaked and it sounds like a more sensible multi-year plan to phase in more robust banknotes. My large-ish pile of Rs. 1 coins remains useless, however.

An Astounding Result — some may have seen this before, but it’s getting some press now. It’s part of the Numberphile series. Terry Tao (as usual) has a pretty definitive post on it.

Avi Wigderson is giving a talk at Rutgers tomorrow, so I thought about this nice lecture of his on Randomness (and pseudorandomness).

There’s been a lot of blogging about the MIT Mystery Hunt (if I wasn’t so hosed starting up here at Rutgers I’d probably blog about it earlier) but if you want the story and philosophy behind this year’s Hunt, look no further than the writeup of Erin Rhode, who was the Director of the whole shebang.

Last year I did a lot of flying, and as a result had many encounters with the TSA. This insider account should be interesting to anyone who flies regularly.

Linkage

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I’m in the process of moving to New Jersey for my new gig at Rutgers. Before I start teaching I have to go help run the the Mystery Hunt, so I am a little frazzled and unable to write “real” blog posts. Maybe later. In the meantime, here are some links.

The folks at Puzzazz have put out a bevy of links for the 200th anniversary of the crossword puzzle.

The UK has issued a pardon to Alan Turing, for, you know, more or less killing him. It’s a pretty weasely piece of writing though.

An important essay on women’s work: “…women are not devalued in the job market because women’s work is seen to have little value. Women’s work is devalued in the job market because women are seen to have little value.”. (h/t AW)

Of late we seem to be learning quite a bit about early hominins and hominids (I had no idea that hominini was a thing, nor that chimps are in the panini tribe, nor that “tribe” is between subfamily and genus). For example,
they have sequenced some old bones in Spain. Extracting sequenceable mitochondrial DNA is pretty tough — I am sure there are some interesting statistical questions in terms of detection and contamination. We’ve also learned that some neanderthals were pretty inbred.

Kenji searches for the perfect chocolate chip cookie recipe.

Linkage

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A map of racial segregation in the US.

Vi Hart explains serial music (h/t Jim CaJacob).

More adventures in trolling scam journals with bogus papers (h/t my father).

Brighten does some number crunching on his research notebook.

Jerry takes “disruptive innovation” to task.

Vladimir Horowitz plays a concert at the Carter White House. Also Jim Lehrer looks very young. The program (as cribbed from YouTube)

  • The Star-Spangled Banner
  • Chopin: Sonata in B-flat minor, opus 35, n°2
  • Chopin: Waltz in a minor, opus 34, n°2
  • Chopin: Waltz in C-sharp minor, opus 64, n° 2
  • Chopin: Polonaise in A-flat major, opus 53 ,Héroïque
  • Schumann: Träumerei, Kinderszene n°7
  • Rachmaninoff: Polka de W.R
  • Horowitz: Variations on a theme from Bizet’s Carmen

The Simons Institute is going strong at Berkeley now. Moritz Hardt has some opinions about what CS theory should say about “big data,” and how it might be require some adjustments to ways of thinking. Suresh responds in part by pointing out some of the successes of the past.

John Holbo is reading Appiah and makes me want to read Appiah. My book queue is already a bit long though…

An important thing to realize about performance art that makes a splash is that it can be often exploitative.

Mimosa shows us what she sees.

Linkage

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Quicksort as a dance. Via James Fallows.

I have a subscription to Harper’s and try to solve the cryptic crossword each month in the vain hope that I will win a free year’s subscription. The puzzles back to 1976 have been posted online.

Tesla and the lone inventor myth.

My friend (and ex-fellow actor) Stephen Larson‘s project OpenWorm was written up in Wired UK.

Max has an important reminder about stochastic kernels and conditional probabilities.

Linkage (technical)

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Having seen a talk recently by John Ioannidis on how medical research is (often) bunk, this finer corrective by Larry Wasserman was nice to read.

Computer science conferences are often not organized by the ACM, but instead there are different foundations for machine learning and vision and so on that basically exist to organize the annual conference(s). At least, that is what I understand. There are a few which are run by the ACM, and there’s often debate about whether or not the ACM affiliation is worth it, given the overheads and so on. Boaz Barak had a post a little over a week ago making the case for sticking with the ACM. Given the hegemonic control of the IEEE on all things EE (more or less), this debate is new to me. As far as I can tell, ISIT exists to cover some of the cost of publishing the IT Transactions, and so it sort of has to be run by IEEE.

As mentioned before, Tara Javidi has a nice post up on what it means for one random variable to be stochastically less variable than another.

Paul Miniero has a bigger picture view of NIPS — I saw there were lots of papers on “deep learning” but it’s not really my area so I missed many of those posters.

David Eppstein’s top 10 cs.DS papers from 2012.

Video : “Matrices and their singular values” (1976)

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Via Allie Fletcher, here is an awesome video on the SVD from Los Alamos National Lab in 1976:

From the caption by Cleve Moler (who also blogs):

This film about the matrix singular value decomposition was made in 1976 at the Los Alamos National Laboratory. Today the SVD is widely used in scientific and engineering computation, but in 1976 the SVD was relatively unknown. A practical algorithm for its computation had been developed only a few years earlier and the LINPACK project was in the early stages of its implementation. The 3-D computer graphics involved hidden line computations. The computer output was 16mm celluloid film.

The graphics are awesome. Moler blogged about some of the history of the film. Those who are particularly “attentive” may note that the SVD movie seems familiar:

The first Star Trek movie came out in 1979. The producers had asked Los Alamos for computer graphics to run on the displays on the bridge of the Enterprise. They chose our SVD movie to run on the science officer’s display. So, if you look over Spock’s shoulder as the Enterprise enters the nebula in search of Viger, you can glimpse a matrix being diagonalized by Givens transformations and the QR iteration.