lidsblog

England and ICASSP

I was in England during Spring break to receive my MA degree. Unlike other degrees awarded by Cambridge University, the MA degree is conferred to anyone who's graduated with a BA degree successfully, no less than six years from the end of our first term of residence. This means that if you live long enough, you'll be conferred the degree approximately 3-4 years after your first degree(s). Which was nice for me as this provided me with an excuse to head back to Cambridge to visit my former classmates who were all very successful in their own right. Unlike me, most of them have sensibly decided to get on with life with a proper job, mostly in investment banking and finance. I also managed to meet up with people from the machine learning group at Microsoft Research Cambridge and got a better idea of the scope of my project this summer.

After less than a day to get over 5 hrs of jetlag, I headed further west to Vegas together with some members of LIDS and SSG. ICASSP is a huge conference with emphasis on signal processing and speech. A subset of the talks and posters were very impressive but what I got out of the conference was the chance to meet and talk with people, graduate students as well as professors. I was nervous before my talk but I guess it's natural. I wasn't terribly happy with the way I handled the questions at the end and I hope to do better for my RQE in 3 weeks time. I will have one more practice run at the upcoming North East Student Colloquium on Artificial Intelligence (NESCAI) to be held in Cornell at  the start of May. I'm looking forward to this conference. Some of the talks sound interesting and high quality. After the ICASSP, SSG students took the opportunity to venture to the Grand Canyon. Just in case you've read the previous post by Kush Varshney and are interested to find out who the biggest (and speediest) loser at Vegas was, it's none other than the current blogger. I know I've been a letdown but I'm not a bad poker player. Serdar Balci can attest to that. I was just unlucky to to screwed by the Queen on the river! But Vegas was great fun. We did everything there was to do. Away from the tables I was lucky - When we passed by the Bellagio fountain one night, the waters were dancing to the tune of "Time to Say Goodbye" by Sarah Brightman and Andrea Bocelli. I listen to this tune, on youtube, whenever I'm stressed.  I encourage you to do so too.   

Alright, as mentioned, I will be taking my RQE in 3 weeks. I should really start panicking and work hard to understand all the nitty-gritty details about my research. But before that, I have one term paper for Information Theory 6.441 and two more midterms (6.441 and 18.100B) to work on. In addition, I have some research to write up before my internship at Microsoft. So it should be an interesting end to the semester.

Vincent

Convex Optimization

Why can't things be like they used to be?  Pan Am and TWA?  Flying without quart-sized, clear, plastic, zip-top bags?  Boarding economy class from the back of the aircraft to the front?  As Pablo mentioned in the last lecture of 6.255, the newfangled zone boarding is the solution to an optimization problem to minimize boarding time.  I don't agree with the model used to describe the constraints and particularly the costs, but I don't doubt that zone boarding is the optimal feasible solution for the given model. 

I had the pleasure (or hassle) of zone boarding four times recently on the way to and on the way back from Las Vegas.  I wasn't there to emulate 21, or to lose a hundred dollars in ten minutes, but to attend the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP). 

The students of LIDS were there in force.  Myung Jin Choi & Venkat Chandrasekaran had a paper Maximum Entropy Relaxation for Multiscale Graphical Model Selection.  Dmitry Malioutov had a paper Compressed Sensing with Sequential Observations.  Mesrob Ohannessian had a paper A Turbo-Style Algorithm for Lexical Baseforms Estimation. Xiaomeng (Shirley) Shi had a paper Joint Base-Calling of Two DNA Sequences with Factor Graphs.  Vincent Tan had a paper Learning Max-Weight Discriminative Forests.  Lav Varshney & I had a paper Minimum Mean Bayes Risk Error Quantization of Prior Probabilities.

Aside from the Elvis impersonators and mimes, one interesting thing at the conference was a panel on convex optimization theory and practice in signal processing.  The main lesson that was imparted was that people working on signal processing applications really need to learn and use modern techniques of convex optimization, as well as collaborate with optimization theorists starting at the initial stages of problem formulation.  (One example I can point to where convex optimization theory has been used is Jason Johnson's Lagrangian relaxation work.) 

LIDS is uniquely positioned in this regard because we have both signal processors and optimizers within one lab.  Some members of LIDS are aeronautical engineers; now if we also had overhead bin designers, we could finally make aircraft boarding hassle-free.