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I guess I should add : - U. Toronto - U. BC

Thanks for correcting me. Ok, so, - CMU - UW - UNC/Duke/NCSU Are there any other approachable schools (lower-ranked is better) you know about doing decent work in this area? (I'd mentioned Berkeley because of Michael I. Jordan. Stanford was an error). Cheers.

Hi, I can't seem to find a decent list of Bayesian stats research groups online. Can you name some (other than the obvious Stanford Berkeley Duke etc.)? I want to browse their pages Thanks!

Yeah machine learning is what I've been studying in my master's degree, that's how I discovered that I don't hate math like I thought I did 8) I've taught myself some relatively high-powered Bayesian stats (at the level of the Bayesian Choice by Robert) and machine learning stuff (variational bayes, expectation propagation, etc.) and my thesis involves applying/developing/improving algorithms in these areas. BUT, I don't have the pure math courses sadly. I've only taken multivariable calc and linear algebra as an undergrad. I don't have e.g. real analysis, complex analysis, abstract algebra, etc. So I need to take a bunch of math courses, but I'd like to take them at grad level in the first 2 years of a PhD program rather than going through the undergrad-level curriculum first or doing a Master's. ML & data mining are cool but I really want to learn more straight-up math so I can apply some more high-powered techniques to the stats. For e.g. nonparametrics my level of maths is simply not high enough. Variational bayes for example was a huge struggle to figure out because I hadn't done mean field theory or variational calc. in college, even though your average physics major gets that stuff quite early on. So I don't want to fight an uphill battle, rather I'd like to be in a PhD program where those courses are intensively taught in the first two years along with grad-level analysis/algebra/etc. To me that sounds like an applied math program .. maybe a Stats PhD would be good too. The main thing is, how do I get in? Master's degree? Just go try to do research somewhere? Bribes? :twisted:

I'd rather take a job as an R.A. or something for a year and get the research experience and then apply and get the school that I want, rather than spending 5 years in a school I don't want...

Dear Recessive Gene, We were sadly unable to admit you this reproductive cycle, due largely to random fluctuations in enzyme concentration. Please accept our best wishes for your future career! Warmest Regards, The Chromosome Admissions Committee.

Hi, So I'm interested in applying to an applied math PhD program somewhere .. or at least a Master's followed by a PhD. The problem is that I haven't any degrees in the subject. I have an undergrad and a master's in computer science. My undergraduate math grades are not amazing (about ~2.75) but my CS grades are around ~3.8. My CS grades in the master's program are 4.0. The thing is that I didn't get math when I was an undergrad, but I do now. My master's has been intensely mathematical, and I want to go on to work in mathematical statistics. I really love working in this area. I don't have any research experience in Math, but I do have theses in computer science. How do I get into a Math PhD program without a Math degree? Thanks.

You need some stats. I'm sure you've taken a basic stats course and an econometrics one. But if you want to do e.g. public policy research, doing e.g. an advanced mathematical statistics course would be really good on your application.

I noticed your location is San Diego - are you at UCSD? If so, is there any hope of getting in there without research experience? That's one place I'd really love to go, but it definitely qualifies as one of the primary schools in a strong state system.

I did one this year. I found that the quality of instruction was generally poor. The opportunities for doing individual projects with profs were very good. It was also useful as a year to teach myself the things I'll need to know in PhD school. I was admitted for a PhD by the same institution. This is probably the only really useful aspect of a coursework master's. If you do it at a place you want to get a PhD, you'll have advocates on the admission committee who've seen you work (conversely, if you screw it up, you're definitely not getting in.)

It's not hard to explain. A lot of the other applicants had mommy and daddy just pony up the cash. You had to really want it. It shows discipline, determination and most importantly motivation. I think you're underestimating yourself. You can put a one-sentence footnote somewhere in your app that mentions that you were working during those years in order to afford the tuition, and they won't hold it against you (probably consider it a plus).

I got a 720V/800Q/6.0, and I didn't pay anyone a dime. Went to university library and picked up every one of their old GRE books, photocopied the exams, did them all ... at least one or two sections (those little 40 min chunks) a day. I didn't prepare the verbal because I read a lot of books and I figured that'd be enough. I think I got lucky because there were a lot of words I didn't know on the test and I guessed. I probably should've prepared it, in hindsight. I did prep the math a lot (did all the math tests from every book). Here's what I figured out: a) Ignore all their crap about how to solve the problems, it's just there to make the book thicker. All you want are the questions. You'll find your own best way of solving problems by doing lots of problems. Read the question. Seriously. c) Don't try tricks. The dumb, straight-forward, brute force approach works best. Imagine yourself to be a student with no guile or creativity. How would you solve this problem? Make tables, list out numbers, etc. If it takes 60 seconds (which is a LONG time), you're totally on target. Most important: d) Reflection. Give the problems names (the same problems show up again and again ... once you nail a fast algorithm for solving, it's easy). Once you've done a section of problems, find out why each wrong one was wrong, and think of faster ways you could've done the correct ones. Circle the wrong ones, put them somewhere, and do them again the next day. Warming up before you take the exam (I got this from a friend for the SATs, and it worked wonders so I do it for every exam): Find 5 or 10 easy EASY questions that you have solved (maybe that you derived satisfaction from figuring out the trick for). Do them about an hour before the exam, and then just relax. Take an iPod and chill out, ignore the other people who are stressed because they're going to fail. You'll do well, no worries.

Do the Math GRE. One place to start is a book called "All the Mathematics You Missed [but need to know for Graduate School]" by Thomas Garrity. It's a small paperback and you can flip through it and get re-acquainted (briefly) with some of the topics you forgot. The Princeton Review book on cracking the Math GRE is solid as well. In the end, though, you already said the answer: best idea is a tutor. Make sure you leave yourself at least one or two practice tests clean (or get more from the REA book). Don't take the test if your practices give you less than mid-700s. The prep will still be useful for your own knowledge and getting you used to studying for tests again

I'm an OK applicant (~3.5 in CS from a Top 20 undergrad, solid quant. GRE, no research) and I want to study machine learning. PhD programs that might accept this profile? (Some weak math grades but strong CS grades). Cities are better than rural for me... Thanks for your advice!

That said ... if you have the option, it might be more useful to dig deeper in one of the subjects than to spread yourself out so much among three different subjects. Which of Economics, Asian Studies and Math is your favorite? I'd take more classes in that one and stop whichever you're least interested in. For Econ, good choices would be Development, Ec. History, Political Economy - even better, the grad-level Macro course. If you haven't done a thesis and still have time, I highly recommend that. Going deep into one field (i.e. way beyond the degree requirements) as well as out into a couple others (as you've already done) means you are focused enough to really "nail" something but still open-minded. This looks good.