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

NLP conferences

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

EM tutorial

Why are the objectives of logistic regression and crf models convex?

LaTeX on blogger

git concepts

Eigen: a c++ matrix library