Randomization has proven to be a pretty fascinating and useful resource to use when designing algorithms. Randomization has been used to create fast algorithms for things like sorting, finding the median of a list, and more interesting problems like matrix multiplication verification, global min-cuts, finding 2-dimensional Delaunay triangulations of a…
So it is February 2020 and if there’s some things I smell in the air these days, it is a mixture of rain, snow.. and a bit of Deep Learning (DL). I’ve been passively observing some of the academic and industry trends of AI and Machine Learning (ML) for a…
Optimization is a fascinating area with a lot of uses, especially these days with Machine Learning (ML). As those involved with ML know, gradient descent variants have been some of the most common optimization techniques employed for training models of all kinds. For very large data sets, stochastic gradient descent…
PhD student @ UIUC who enjoys the mystical arts of mathematics. Works in Theoretical Computer Science. www.christianjhoward.me
