Boyd and Vandenberghe's book "Convex Optimization"
Groups, rings, fields, and vector spaces
Math unicode symbols (handy for preparing slides).
Tips and tricks in stochastic gradient descent land.
How to use stochastic gradient descent with L1-regularization? prox-grad, dual averaging, FRTL
installing standard R packages, custom packages in R, and what to do when cpp compilation fails while installing custom R packages
locality sensitive hashing (LSH)
history of deep learning
count-min sketches (a cool data structure that approximates counts of elements in a set)
style guidelines for python
an introduction to GCC
simulations of beta (and other) distribution density
evaluating clusterings (a ps version of the paper which I like more)
sequence labeling tutorial
configure; make; make install
step-by-step example for using GDB within Emacs to debug a C or C++ program
gentle tutorial on using valgrind to find memory problems in c++ code
using screen to survive dropped ssh connections while running your jobs
productivity tips for using ssh
blacklight frontend machine blacklight.psc.teragrid.org
learning topic models; beyond svd. slides, paper
mit's matrix cookbook
Why are the objectives of logistic regression and crf models convex?
LaTeX on blogger
Eigen: a c++ matrix library